lme_mods

Packages & Setup

# install.packages(c("tidyverse","purrr","R.matlab","readxl","dplyr"))
library(readxl);
library(purrr)
library(tidyverse);

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## ✔ ggplot2   3.5.0     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
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library(tibble)
library(knitr);
library(gtsummary)
library(kableExtra)

## 
## Attaching package: 'kableExtra'
## 
## The following object is masked from 'package:dplyr':
## 
##     group_rows

library(lme4)

## Loading required package: Matrix
## 
## Attaching package: 'Matrix'
## 
## The following objects are masked from 'package:tidyr':
## 
##     expand, pack, unpack

GTSUMMARY THEME

# my_theme <-
#   list(
#     "tbl_summary-str:default_con_type" = "continuous2",
#     "tbl_summary-str:continuous_stat" = c(
#       "{median} ({p25} - {p75})",
#       "{mean} ({sd})",
#       "{min} - {max}"
#     ),
#     "tbl_summary-str:categorical_stat" = "{n} / {N} ({p}%)",
#     "style_number-arg:big.mark" = "",
#     "tbl_summary-fn:percent_fun" = function(x) style_percent(x, digits = 3)
#   )
# my_theme <-
#   list()
# gtsummary::set_gtsummary_theme(my_theme)
gtsummary::set_gtsummary_theme(theme_gtsummary_journal("jama"))

## Setting theme `JAMA`
## Setting theme `JAMA`

# reset_gtsummary_theme()

load table

# excel_dir <-"M:/jsalminen/GitHub/par_EEGProcessing/src/_data/MIM_dataset/_studies/04162024_MIM_YAOAN89_antsnormalize_iccREMG0p4_powpow0p3_skull0p01/cluster/icrej_5/12/spec_data/group_spec/psd_calcs/fooof_kinematics_table.xlsx";
excel_dir <-"M:/jsalminen/GitHub/par_EEGProcessing/src/_data/MIM_dataset/_studies/04232024_MIM_YAOAN89_antsnorm_dipfix_iccREMG0p4_powpow0p3_skull0p01_15mmrej/cluster/icrej_5/11/spec_data/group_spec/psd_calcs/fooof_kinematics_table_nans.xlsx";
eegt <- read_excel(excel_dir,sheet="Sheet1") 

get unique entries

clusters = unique(eegt$cluster_id);
subjects = unique(eegt$subj_char);
groups = unique(eegt$group_char);
kin_measures = c('mean_APexc_COV','mean_APexc_mean','mean_MLexc_COV','mean_MLexc_mean','mean_StepDur','mean_UDexc_COV','mean_UDexc_mean','mean_StanceDur','mean_GaitCycleDur','mean_PeakUpDownVel_mean');
kin_title_chars = c("AP Exc. COV","AP Exc. Mean","ML Exc. COV","ML Exc. Mean","Step Dur.","UD Exc. COV","UD Exc Mean","Stance Dur.","Gait Cycle Dur.","Peak UD Vel. Mean")
kin_inds_plot = c(1:length(kin_measures));
eeg_measures = c('theta_avg_power','alpha_avg_power','beta_avg_power','beta_div_theta','theta_div_beta','log_beta_div_theta','log_theta_div_beta','aperiodic_exp','aperiodic_offset');
eeg_title_chars = c("**THETA**","**ALPHA**","**BETA**","**BETA/THETA**","**THETA/BETA**","**log10(BETA/THETA)**","**log10(THETA/BETA)**","**AP exp**","**AP offset**");
eeg_inds_plot = c(4:7);

get speeds only

eegt <- filter_at(eegt,vars('cond_char'), any_vars(. %in% c('0.25','0.5','0.75','1.0')))
flat_speeds = unique(eegt$cond_char)
eegt$cond_char <- as.numeric(eegt$cond_char)
eegt$speed_cond_num <- as.numeric(eegt$cond_char)
eegt <- mutate(eegt,across(c('subj_char'), factor))
eegt <- mutate(eegt,across(c('group_char'), factor))
eegt$speed_ord <- cut(eegt$cond_char, 4, ordered = TRUE)
eegt <- mutate(eegt,across(c('cond_char'), factor))
eegt$group_speed_code = paste(eegt$group_char,eegt$cond_char,sep="_")
head(eegt)

create ratios

Log <- function(x, base = exp(1)) {
  LOG <- base::log(as.complex(x), base = base)
  if (all(Im(LOG) == 0)) { LOG <- Re(LOG) }
  LOG }
#%% CALCS
eegt <- eegt%>%
  mutate(beta_div_theta=beta_avg_power/theta_avg_power)
eegt <- eegt%>%
  mutate(theta_div_beta=theta_avg_power/beta_avg_power)
eegt <- eegt%>%
  mutate(log_beta_div_theta=log10(beta_avg_power/theta_avg_power+max(abs(beta_avg_power/theta_avg_power))))
eegt <- eegt%>%
  mutate(log_theta_div_beta=log10(theta_avg_power/beta_avg_power+max(abs(theta_avg_power/beta_avg_power))))
# eegt <- eegt%>%
#   mutate(log_beta_div_theta=log10(beta_avg_power/theta_avg_power+mean(abs(beta_avg_power/theta_avg_power))/(mean(abs(beta_avg_power/theta_avg_power))+3*sd(abs(beta_avg_power/theta_avg_power)))));
# eegt <- eegt%>%
#   mutate(log_theta_div_beta=log10(theta_avg_power/beta_avg_power+mean(abs(theta_avg_power/beta_avg_power))/(mean(abs(theta_avg_power/beta_avg_power))+3*sd(abs(theta_avg_power/beta_avg_power)))));
# eegt <- eegt%>%
#   mutate(log_beta_div_theta=log10((beta_avg_power/theta_avg_power)+abs(min((beta_avg_power/theta_avg_power)))));
# eegt <- eegt%>%
#   mutate(log_theta_div_beta=log10((theta_avg_power/beta_avg_power)+abs(min((theta_avg_power/beta_avg_power)))));
eegt <- eegt%>%
  mutate(log_beta_div_theta=Re(Log((beta_avg_power/theta_avg_power),10)*Conj(Log((theta_avg_power/beta_avg_power),10))));
eegt <- eegt%>%
  mutate(log_theta_div_beta=Re(Log((theta_avg_power/beta_avg_power),10)*Conj(Log((theta_avg_power/beta_avg_power),10))));

LME EEG ~ 1+kin+group+kin:group

Changes in theta_avg_power for Cluster: 3
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-66 (-230 to 98)	0.43	0.90	0.12 (-3.3 to 3.5)	0.95	0.95	-1.0 (-2.0 to -0.09)	0.032	0.13	2.0 (0.82 to 3.1)	<0.001	0.003
mean_APexc_COV	2.5 (-7.3 to 12)	0.62	0.90	0.01 (-0.20 to 0.21)	0.95	0.95	0.01 (-0.04 to 0.07)	0.65	0.87	-0.02 (-0.08 to 0.05)	0.62	0.82
group_char		0.75	0.90		0.75	0.95		0.57	0.87		0.33	0.66
H1000’s	—			—			—			—
H2000’s	89 (-169 to 346)			0.55 (-4.8 to 5.9)			0.58 (-0.95 to 2.1)			-0.77 (-2.6 to 1.1)
H3000’s	71 (-149 to 292)			-1.3 (-5.8 to 3.3)			0.68 (-0.63 to 2.0)			-1.2 (-2.9 to 0.41)
mean_APexc_COV * group_char		0.90	0.90		0.64	0.95		0.96	0.96		0.97	0.97
mean_APexc_COV * H2000’s	-2.5 (-15 to 10)			-0.01 (-0.28 to 0.26)			-0.01 (-0.09 to 0.07)			0.01 (-0.08 to 0.09)
mean_APexc_COV * H3000’s	-2.6 (-14 to 8.6)			0.08 (-0.16 to 0.31)			-0.01 (-0.08 to 0.06)			0.01 (-0.07 to 0.08)
subj_char.sd__(Intercept)	34 (NA to NA)			0.00 (NA to NA)			0.49 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	206 (NA to NA)			4.4 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in alpha_avg_power for Cluster: 3
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	128 (-16 to 271)	0.081	0.16	0.12 (-2.9 to 3.2)	0.94	0.95	-0.28 (-1.1 to 0.53)	0.49	0.66	1.0 (0.09 to 2.0)	0.033	0.13
mean_APexc_mean	-2,788 (-5,298 to -277)	0.030	0.12	1.6 (-52 to 55)	0.95	0.95	-10 (-24 to 3.8)	0.15	0.62	12 (-2.3 to 26)	0.10	0.20
group_char		0.39	0.39		0.86	0.95		0.95	0.95		0.88	0.88
H1000’s	—			—			—			—
H2000’s	-103 (-300 to 95)			-0.24 (-4.4 to 3.9)			-0.19 (-1.3 to 0.96)			-0.11 (-1.5 to 1.3)
H3000’s	-125 (-308 to 57)			0.72 (-3.1 to 4.6)			-0.06 (-1.1 to 1.0)			-0.34 (-1.7 to 0.98)
mean_APexc_mean * group_char		0.23	0.31		0.93	0.95		0.44	0.66		0.37	0.49
mean_APexc_mean * H2000’s	2,755 (-1,085 to 6,594)			15 (-66 to 96)			12 (-9.9 to 34)			-11 (-34 to 13)
mean_APexc_mean * H3000’s	2,780 (-816 to 6,376)			2.3 (-74 to 78)			12 (-9.1 to 32)			-16 (-39 to 7.2)
subj_char.sd__(Intercept)	26 (NA to NA)			0.00 (NA to NA)			0.49 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	206 (NA to NA)			4.4 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_avg_power for Cluster: 3
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-150 (-278 to -22)	0.022	0.087	0.12 (-2.5 to 2.8)	0.93	0.95	-0.75 (-1.5 to 0.05)	0.066	0.27	2.2 (1.1 to 3.3)	<0.001	<0.001
mean_MLexc_COV	8.7 (0.20 to 17)	0.045	0.090	0.01 (-0.17 to 0.18)	0.95	0.95	-0.01 (-0.06 to 0.05)	0.82	0.82	-0.03 (-0.10 to 0.03)	0.29	0.29
group_char		0.25	0.34		0.91	0.95		0.34	0.65		0.025	0.051
H1000’s	—			—			—			—
H2000’s	96 (-86 to 277)			0.66 (-3.1 to 4.4)			0.82 (-0.29 to 1.9)			-1.7 (-3.1 to -0.24)
H3000’s	155 (-30 to 339)			-0.11 (-4.0 to 3.7)			0.31 (-0.81 to 1.4)			-1.8 (-3.3 to -0.38)
mean_MLexc_COV * group_char		0.36	0.36		0.81	0.95		0.48	0.65		0.28	0.29
mean_MLexc_COV * H2000’s	-3.4 (-15 to 8.5)			-0.02 (-0.27 to 0.23)			-0.03 (-0.10 to 0.05)			0.07 (-0.02 to 0.15)
mean_MLexc_COV * H3000’s	-8.9 (-21 to 3.4)			0.06 (-0.19 to 0.32)			0.02 (-0.06 to 0.09)			0.05 (-0.04 to 0.13)
subj_char.sd__(Intercept)	32 (NA to NA)			0.00 (NA to NA)			0.50 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	204 (NA to NA)			4.4 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_div_theta for Cluster: 3
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	152 (30 to 274)	0.015	0.030	0.21 (-2.4 to 2.8)	0.88	0.99	-0.33 (-1.1 to 0.40)	0.38	0.50	0.80 (-0.11 to 1.7)	0.085	0.11
mean_MLexc_mean	-2,174 (-3,593 to -755)	0.003	0.011	0.05 (-30 to 30)	0.99	0.99	-6.2 (-14 to 2.0)	0.14	0.41	11 (2.1 to 20)	0.015	0.061
group_char		0.18	0.18		0.96	0.99		0.69	0.69		0.70	0.70
H1000’s	—			—			—			—
H2000’s	-94 (-256 to 69)			0.12 (-3.3 to 3.6)			-0.34 (-1.3 to 0.63)			0.39 (-0.85 to 1.6)
H3000’s	-149 (-307 to 9.0)			0.46 (-2.9 to 3.8)			0.01 (-0.94 to 0.97)			-0.09 (-1.3 to 1.1)
mean_MLexc_mean * group_char		0.050	0.067		0.98	0.99		0.21	0.41		0.042	0.083
mean_MLexc_mean * H2000’s	1,796 (23 to 3,569)			2.9 (-35 to 41)			9.3 (-0.98 to 20)			-13 (-24 to -2.2)
mean_MLexc_mean * H3000’s	2,162 (369 to 3,956)			3.9 (-34 to 42)			6.7 (-3.8 to 17)			-13 (-25 to -1.3)
subj_char.sd__(Intercept)	22 (NA to NA)			0.00 (NA to NA)			0.50 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	204 (NA to NA)			4.4 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_div_beta for Cluster: 3
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	0.02 (-117 to 117)	0.99	0.99	0.24 (-2.2 to 2.7)	0.85	0.99	-0.41 (-1.1 to 0.24)	0.22	0.42	1.3 (0.54 to 2.2)	0.001	0.004
mean_StepDur	-28 (-148 to 92)	0.65	0.99	-0.03 (-2.6 to 2.5)	0.98	0.99	-0.46 (-1.1 to 0.19)	0.16	0.42	0.39 (-0.27 to 1.0)	0.25	0.50
group_char		0.67	0.99		0.89	0.99		0.74	0.74		0.72	0.72
H1000’s	—			—			—			—
H2000’s	85 (-112 to 281)			0.30 (-3.8 to 4.4)			-0.35 (-1.5 to 0.75)			-0.12 (-1.4 to 1.2)
H3000’s	2.4 (-187 to 192)			0.95 (-3.0 to 4.9)			0.11 (-0.97 to 1.2)			-0.54 (-1.8 to 0.77)
mean_StepDur * group_char		0.85	0.99		0.99	0.99		0.31	0.42		0.41	0.55
mean_StepDur * H2000’s	-53 (-287 to 181)			0.12 (-4.8 to 5.1)			0.96 (-0.32 to 2.2)			-0.71 (-2.0 to 0.61)
mean_StepDur * H3000’s	27 (-214 to 268)			-0.24 (-5.3 to 4.8)			0.50 (-0.85 to 1.9)			-0.76 (-2.2 to 0.68)
subj_char.sd__(Intercept)	33 (NA to NA)			0.00 (NA to NA)			0.49 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	206 (NA to NA)			4.4 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_beta_div_theta for Cluster: 3
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-21 (-119 to 76)	0.67	0.93	0.19 (-1.8 to 2.2)	0.85	0.99	-0.74 (-1.3 to -0.18)	0.010	0.040	1.4 (0.71 to 2.2)	<0.001	<0.001
mean_UDexc_COV	-0.33 (-7.3 to 6.7)	0.93	0.93	0.00 (-0.15 to 0.15)	0.99	0.99	-0.01 (-0.05 to 0.03)	0.69	0.69	0.02 (-0.02 to 0.06)	0.34	0.50
group_char		0.40	0.93		0.58	0.99		0.44	0.59		0.56	0.56
H1000’s	—			—			—			—
H2000’s	102 (-48 to 251)			0.20 (-2.9 to 3.3)			-0.08 (-0.94 to 0.78)			-0.27 (-1.4 to 0.85)
H3000’s	25 (-128 to 177)			-1.4 (-4.6 to 1.7)			0.48 (-0.40 to 1.4)			-0.62 (-1.7 to 0.51)
mean_UDexc_COV * group_char		0.70	0.93		0.32	0.99		0.37	0.59		0.37	0.50
mean_UDexc_COV * H2000’s	-3.8 (-14 to 6.5)			0.01 (-0.20 to 0.23)			0.04 (-0.02 to 0.10)			-0.03 (-0.09 to 0.03)
mean_UDexc_COV * H3000’s	0.23 (-10 to 11)			0.16 (-0.06 to 0.38)			0.01 (-0.05 to 0.07)			-0.04 (-0.10 to 0.02)
subj_char.sd__(Intercept)	33 (NA to NA)			0.00 (NA to NA)			0.48 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	206 (NA to NA)			4.4 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_theta_div_beta for Cluster: 3
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-1.6 (-114 to 111)	0.98	0.98	0.14 (-2.2 to 2.5)	0.91	0.95	-0.97 (-1.6 to -0.32)	0.003	0.013	2.3 (1.5 to 3.1)	<0.001	<0.001
mean_UDexc_mean	-1,008 (-5,440 to 3,424)	0.66	0.98	2.8 (-91 to 97)	0.95	0.95	5.5 (-19 to 30)	0.66	0.66	-24 (-49 to 1.6)	0.067	0.067
group_char		0.80	0.98		0.63	0.95		0.057	0.11		0.002	0.003
H1000’s	—			—			—			—
H2000’s	-46 (-208 to 116)			0.00 (-3.4 to 3.4)			1.1 (0.21 to 2.1)			-1.7 (-2.9 to -0.50)
H3000’s	4.9 (-153 to 162)			1.4 (-1.9 to 4.7)			0.54 (-0.37 to 1.5)			-2.0 (-3.1 to -0.81)
mean_UDexc_mean * group_char		0.44	0.98		0.82	0.95		0.16	0.22		0.062	0.067
mean_UDexc_mean * H2000’s	3,946 (-2,338 to 10,231)			16 (-116 to 149)			-29 (-64 to 6.0)			40 (4.2 to 77)
mean_UDexc_mean * H3000’s	953 (-5,165 to 7,072)			-25 (-154 to 104)			0.75 (-34 to 35)			34 (-2.2 to 71)
subj_char.sd__(Intercept)	36 (NA to NA)			0.00 (NA to NA)			0.50 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	205 (NA to NA)			4.4 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_exp for Cluster: 3
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-8.9 (-107 to 89)	0.86	0.86	0.22 (-1.8 to 2.3)	0.83	0.99	-0.49 (-1.0 to 0.07)	0.087	0.31	1.4 (0.71 to 2.2)	<0.001	<0.001
mean_StanceDur	-13 (-85 to 58)	0.72	0.86	-0.01 (-1.5 to 1.5)	0.99	0.99	-0.28 (-0.67 to 0.11)	0.15	0.31	0.21 (-0.18 to 0.61)	0.29	0.52
group_char		0.59	0.86		0.84	0.99		0.74	0.74		0.52	0.52
H1000’s	—			—			—			—
H2000’s	82 (-80 to 245)			0.62 (-2.8 to 4.0)			-0.23 (-1.2 to 0.69)			-0.24 (-1.4 to 0.92)
H3000’s	11 (-148 to 171)			0.97 (-2.4 to 4.3)			0.17 (-0.74 to 1.1)			-0.67 (-1.8 to 0.48)
mean_StanceDur * group_char		0.84	0.86		0.98	0.99		0.27	0.37		0.41	0.52
mean_StanceDur * H2000’s	-35 (-174 to 103)			-0.23 (-3.2 to 2.7)			0.60 (-0.16 to 1.4)			-0.42 (-1.2 to 0.36)
mean_StanceDur * H3000’s	13 (-134 to 160)			-0.20 (-3.3 to 2.9)			0.32 (-0.49 to 1.1)			-0.45 (-1.3 to 0.40)
subj_char.sd__(Intercept)	32 (NA to NA)			0.00 (NA to NA)			0.49 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	206 (NA to NA)			4.4 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_offset for Cluster: 3
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	0.06 (-117 to 117)	0.99	0.99	0.24 (-2.2 to 2.7)	0.85	0.99	-0.41 (-1.1 to 0.24)	0.22	0.42	1.3 (0.54 to 2.2)	0.001	0.004
mean_GaitCycleDur	-14 (-74 to 46)	0.65	0.99	-0.01 (-1.3 to 1.3)	0.98	0.99	-0.23 (-0.56 to 0.09)	0.16	0.42	0.19 (-0.14 to 0.52)	0.25	0.50
group_char		0.67	0.99		0.89	0.99		0.74	0.74		0.71	0.71
H1000’s	—			—			—			—
H2000’s	84 (-112 to 281)			0.29 (-3.8 to 4.4)			-0.35 (-1.5 to 0.75)			-0.13 (-1.4 to 1.2)
H3000’s	2.4 (-187 to 192)			0.97 (-3.0 to 4.9)			0.11 (-0.97 to 1.2)			-0.54 (-1.8 to 0.77)
mean_GaitCycleDur * group_char		0.85	0.99		0.99	0.99		0.32	0.42		0.41	0.55
mean_GaitCycleDur * H2000’s	-26 (-143 to 90)			0.06 (-2.4 to 2.5)			0.48 (-0.16 to 1.1)			-0.35 (-1.0 to 0.31)
mean_GaitCycleDur * H3000’s	14 (-107 to 134)			-0.13 (-2.7 to 2.4)			0.25 (-0.43 to 0.93)			-0.38 (-1.1 to 0.34)
subj_char.sd__(Intercept)	33 (NA to NA)			0.00 (NA to NA)			0.49 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	206 (NA to NA)			4.4 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in NA for Cluster: 3
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-53 (-146 to 39)	0.26	0.70	0.16 (-1.8 to 2.1)	0.88	0.97	-1.0 (-1.5 to -0.47)	<0.001	<0.001	2.1 (1.4 to 2.8)	<0.001	<0.001
mean_PeakUpDownVel_mean	119 (-235 to 473)	0.51	0.70	0.24 (-7.3 to 7.8)	0.95	0.97	0.70 (-1.2 to 2.6)	0.48	0.48	-1.9 (-3.8 to 0.10)	0.063	0.065
group_char		0.70	0.70		0.73	0.97		0.029	0.058		0.001	0.002
H1000’s	—			—			—			—
H2000’s	20 (-116 to 157)			0.64 (-2.2 to 3.5)			1.1 (0.27 to 1.8)			-1.4 (-2.5 to -0.40)
H3000’s	56 (-75 to 188)			1.1 (-1.6 to 3.9)			0.63 (-0.13 to 1.4)			-1.8 (-2.8 to -0.78)
mean_PeakUpDownVel_mean * group_char		0.65	0.70		0.97	0.97		0.16	0.21		0.065	0.065
mean_PeakUpDownVel_mean * H2000’s	100 (-394 to 593)			-0.99 (-11 to 9.5)			-2.4 (-5.1 to 0.29)			3.0 (0.25 to 5.7)
mean_PeakUpDownVel_mean * H3000’s	-123 (-599 to 353)			-1.3 (-11 to 8.8)			-0.33 (-3.0 to 2.3)			2.7 (-0.07 to 5.4)
subj_char.sd__(Intercept)	36 (NA to NA)			0.00 (NA to NA)			0.49 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	205 (NA to NA)			4.4 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_avg_power for Cluster: 4
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	3.4 (-286 to 293)	0.98	0.98	-0.04 (-1.1 to 1.0)	0.94	0.94	-0.68 (-2.0 to 0.61)	0.30	0.99	1.0 (-0.28 to 2.3)	0.13	0.42
mean_APexc_COV	0.32 (-17 to 18)	0.97	0.98	0.03 (-0.04 to 0.09)	0.38	0.84	0.01 (-0.07 to 0.08)	0.85	0.99	0.02 (-0.05 to 0.10)	0.55	0.55
group_char		0.47	0.98		0.65	0.87		0.99	0.99		0.21	0.42
H1000’s	—			—			—			—
H2000’s	-2.0 (-487 to 483)			-0.08 (-1.8 to 1.7)			-0.03 (-2.2 to 2.2)			1.9 (-0.28 to 4.0)
H3000’s	219 (-174 to 612)			0.57 (-0.84 to 2.0)			0.04 (-1.8 to 1.9)			1.1 (-0.78 to 2.9)
mean_APexc_COV * group_char		0.73	0.98		0.42	0.84		0.99	0.99		0.55	0.55
mean_APexc_COV * H2000’s	-0.05 (-25 to 25)			-0.01 (-0.10 to 0.08)			0.01 (-0.10 to 0.11)			-0.05 (-0.15 to 0.05)
mean_APexc_COV * H3000’s	-6.6 (-27 to 14)			-0.04 (-0.12 to 0.03)			0.00 (-0.09 to 0.09)			-0.01 (-0.09 to 0.08)
subj_char.sd__(Intercept)	15 (NA to NA)			0.16 (NA to NA)			1.1 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	353 (NA to NA)			1.3 (NA to NA)			1.2 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in alpha_avg_power for Cluster: 4
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	2.6 (-243 to 249)	0.98	0.98	0.22 (-0.66 to 1.1)	0.63	0.86	-0.41 (-1.4 to 0.62)	0.44	0.89	1.0 (0.00 to 2.0)	0.049	0.20
mean_APexc_mean	106 (-4,202 to 4,415)	0.96	0.98	3.6 (-12 to 19)	0.64	0.86	-2.9 (-19 to 14)	0.73	0.89	6.0 (-9.8 to 22)	0.46	0.53
group_char		0.79	0.98		0.91	0.91		0.89	0.89		0.15	0.30
H1000’s	—			—			—			—
H2000’s	32 (-311 to 375)			0.20 (-1.0 to 1.4)			-0.16 (-1.7 to 1.3)			1.4 (-0.05 to 2.9)
H3000’s	-77 (-403 to 249)			0.25 (-0.91 to 1.4)			0.22 (-1.3 to 1.7)			1.0 (-0.47 to 2.5)
mean_APexc_mean * group_char		0.48	0.98		0.61	0.86		0.80	0.89		0.53	0.53
mean_APexc_mean * H2000’s	-708 (-7,271 to 5,856)			-7.3 (-31 to 16)			6.7 (-19 to 33)			-11 (-36 to 15)
mean_APexc_mean * H3000’s	3,333 (-3,253 to 9,920)			-12 (-35 to 12)			-3.3 (-31 to 25)			5.7 (-21 to 33)
subj_char.sd__(Intercept)	45 (NA to NA)			0.17 (NA to NA)			1.1 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	350 (NA to NA)			1.3 (NA to NA)			1.2 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_avg_power for Cluster: 4
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	22 (-177 to 221)	0.83	0.89	-0.05 (-0.77 to 0.66)	0.88	0.88	-0.84 (-1.9 to 0.21)	0.12	0.47	2.2 (1.1 to 3.2)	<0.001	<0.001
mean_MLexc_COV	-0.92 (-14 to 12)	0.89	0.89	0.03 (-0.01 to 0.08)	0.17	0.65	0.02 (-0.04 to 0.08)	0.56	0.56	-0.06 (-0.12 to 0.01)	0.082	0.16
group_char		0.080	0.29		0.48	0.65		0.49	0.56		0.31	0.31
H1000’s	—			—			—			—
H2000’s	-46 (-354 to 261)			0.53 (-0.57 to 1.6)			0.71 (-0.83 to 2.2)			-0.20 (-1.7 to 1.3)
H3000’s	302 (-8.3 to 612)			-0.16 (-1.3 to 0.95)			-0.20 (-1.7 to 1.3)			0.94 (-0.59 to 2.5)
mean_MLexc_COV * group_char		0.14	0.29		0.41	0.65		0.45	0.56		0.23	0.30
mean_MLexc_COV * H2000’s	3.2 (-17 to 24)			-0.05 (-0.12 to 0.03)			-0.04 (-0.13 to 0.06)			0.08 (-0.02 to 0.17)
mean_MLexc_COV * H3000’s	-18 (-38 to 2.9)			-0.01 (-0.08 to 0.07)			0.02 (-0.07 to 0.12)			0.01 (-0.08 to 0.10)
subj_char.sd__(Intercept)	11 (NA to NA)			0.12 (NA to NA)			1.1 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	351 (NA to NA)			1.3 (NA to NA)			1.2 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_div_theta for Cluster: 4
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-1.9 (-214 to 210)	0.99	0.99	0.25 (-0.51 to 1.0)	0.51	0.89	-0.44 (-1.4 to 0.54)	0.38	0.51	0.79 (-0.19 to 1.8)	0.11	0.15
mean_MLexc_mean	129 (-2,369 to 2,626)	0.92	0.99	2.0 (-7.0 to 11)	0.66	0.89	-1.6 (-12 to 8.9)	0.76	0.76	7.0 (-3.1 to 17)	0.17	0.17
group_char		0.34	0.68		0.94	0.94		0.23	0.47		0.039	0.15
H1000’s	—			—			—			—
H2000’s	35 (-259 to 330)			0.06 (-1.0 to 1.1)			-0.36 (-1.7 to 1.0)			1.8 (0.42 to 3.2)
H3000’s	-157 (-439 to 125)			0.17 (-0.84 to 1.2)			0.75 (-0.58 to 2.1)			0.95 (-0.40 to 2.3)
mean_MLexc_mean * group_char		0.10	0.42		0.66	0.89		0.094	0.38		0.077	0.15
mean_MLexc_mean * H2000’s	-412 (-3,642 to 2,817)			-2.7 (-14 to 9.0)			5.9 (-7.4 to 19)			-11 (-23 to 2.3)
mean_MLexc_mean * H3000’s	2,531 (-688 to 5,749)			-5.3 (-17 to 6.2)			-7.4 (-21 to 6.2)			2.0 (-11 to 15)
subj_char.sd__(Intercept)	58 (NA to NA)			0.18 (NA to NA)			1.1 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	345 (NA to NA)			1.2 (NA to NA)			1.2 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_div_beta for Cluster: 4
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	2.6 (-196 to 201)	0.98	0.98	0.57 (-0.15 to 1.3)	0.12	0.49	-0.34 (-1.2 to 0.50)	0.43	0.51	1.2 (0.39 to 2.1)	0.004	0.016
mean_StepDur	6.4 (-198 to 210)	0.95	0.98	-0.17 (-0.91 to 0.57)	0.65	0.96	-0.25 (-0.99 to 0.49)	0.51	0.51	0.13 (-0.58 to 0.83)	0.73	0.73
group_char		0.037	0.073		0.96	0.96		0.15	0.31		0.17	0.22
H1000’s	—			—			—			—
H2000’s	27 (-321 to 376)			-0.17 (-1.4 to 1.1)			-0.24 (-1.7 to 1.2)			1.2 (-0.21 to 2.7)
H3000’s	-405 (-741 to -69)			-0.12 (-1.3 to 1.1)			1.2 (-0.20 to 2.7)			-0.18 (-1.6 to 1.3)
mean_StepDur * group_char		0.006	0.025		0.94	0.96		0.086	0.31		0.036	0.071
mean_StepDur * H2000’s	-36 (-448 to 376)			-0.02 (-1.5 to 1.5)			0.48 (-1.1 to 2.0)			-0.41 (-1.9 to 1.1)
mean_StepDur * H3000’s	675 (242 to 1,108)			-0.28 (-1.9 to 1.3)			-1.7 (-3.4 to 0.01)			2.0 (0.33 to 3.6)
subj_char.sd__(Intercept)	26 (NA to NA)			0.14 (NA to NA)			1.1 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	345 (NA to NA)			1.3 (NA to NA)			1.2 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_beta_div_theta for Cluster: 4
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	9.2 (-158 to 176)	0.91	0.99	0.57 (-0.03 to 1.2)	0.063	0.25	-0.60 (-1.4 to 0.16)	0.12	0.16	1.1 (0.34 to 1.9)	0.005	0.012
mean_UDexc_COV	-0.06 (-12 to 12)	0.99	0.99	-0.01 (-0.06 to 0.03)	0.58	0.85	0.00 (-0.04 to 0.05)	0.90	0.90	0.02 (-0.02 to 0.06)	0.37	0.37
group_char		0.20	0.40		0.85	0.85		0.092	0.16		0.056	0.075
H1000’s	—			—			—			—
H2000’s	8.1 (-246 to 263)			-0.26 (-1.2 to 0.66)			0.04 (-1.1 to 1.2)			1.3 (0.11 to 2.5)
H3000’s	-221 (-491 to 48)			-0.07 (-1.0 to 0.90)			1.2 (0.04 to 2.5)			-0.05 (-1.3 to 1.2)
mean_UDexc_COV * group_char		0.062	0.25		0.84	0.85		0.037	0.15		0.006	0.012
mean_UDexc_COV * H2000’s	-0.69 (-19 to 17)			0.01 (-0.06 to 0.07)			0.01 (-0.06 to 0.08)			-0.03 (-0.09 to 0.03)
mean_UDexc_COV * H3000’s	20 (1.2 to 38)			-0.01 (-0.08 to 0.05)			-0.08 (-0.15 to -0.01)			0.08 (0.02 to 0.15)
subj_char.sd__(Intercept)	40 (NA to NA)			0.13 (NA to NA)			1.1 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	347 (NA to NA)			1.3 (NA to NA)			1.2 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_theta_div_beta for Cluster: 4
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	2.7 (-198 to 203)	0.98	0.98	0.38 (-0.34 to 1.1)	0.30	0.71	-0.80 (-1.7 to 0.06)	0.068	0.27	2.0 (1.1 to 2.8)	<0.001	<0.001
mean_UDexc_mean	240 (-7,586 to 8,066)	0.95	0.98	1.4 (-27 to 29)	0.92	0.92	10 (-20 to 39)	0.51	0.51	-26 (-54 to 2.0)	0.069	0.069
group_char		0.086	0.32		0.35	0.71		0.30	0.40		0.015	0.031
H1000’s	—			—			—			—
H2000’s	6.5 (-291 to 304)			-0.70 (-1.8 to 0.37)			0.45 (-0.84 to 1.7)			0.36 (-0.94 to 1.6)
H3000’s	282 (0.57 to 563)			-0.61 (-1.6 to 0.39)			-0.58 (-1.8 to 0.67)			1.8 (0.52 to 3.0)
mean_UDexc_mean * group_char		0.16	0.32		0.58	0.77		0.16	0.31		0.068	0.069
mean_UDexc_mean * H2000’s	-314 (-11,625 to 10,997)			21 (-19 to 62)			-12 (-54 to 31)			23 (-17 to 64)
mean_UDexc_mean * H3000’s	-9,439 (-20,380 to 1,502)			14 (-25 to 53)			29 (-13 to 72)			-26 (-66 to 15)
subj_char.sd__(Intercept)	42 (NA to NA)			0.09 (NA to NA)			1.1 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	348 (NA to NA)			1.3 (NA to NA)			1.2 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_exp for Cluster: 4
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	2.7 (-164 to 169)	0.98	0.98	0.56 (-0.04 to 1.2)	0.069	0.28	-0.36 (-1.1 to 0.38)	0.34	0.46	1.3 (0.50 to 2.0)	0.001	0.004
mean_StanceDur	4.6 (-117 to 126)	0.94	0.98	-0.12 (-0.56 to 0.32)	0.61	0.92	-0.16 (-0.60 to 0.27)	0.46	0.46	0.08 (-0.34 to 0.50)	0.72	0.72
group_char		0.071	0.14		0.90	0.92		0.24	0.46		0.13	0.18
H1000’s	—			—			—			—
H2000’s	17 (-270 to 303)			-0.23 (-1.3 to 0.81)			-0.14 (-1.4 to 1.1)			1.2 (-0.03 to 2.5)
H3000’s	-307 (-591 to -24)			-0.14 (-1.2 to 0.89)			0.94 (-0.29 to 2.2)			0.07 (-1.2 to 1.3)
mean_StanceDur * group_char		0.011	0.042		0.92	0.92		0.12	0.46		0.028	0.056
mean_StanceDur * H2000’s	-16 (-259 to 227)			0.04 (-0.84 to 0.92)			0.26 (-0.64 to 1.2)			-0.29 (-1.1 to 0.57)
mean_StanceDur * H3000’s	393 (128 to 659)			-0.18 (-1.1 to 0.78)			-0.93 (-1.9 to 0.08)			1.2 (0.22 to 2.1)
subj_char.sd__(Intercept)	28 (NA to NA)			0.14 (NA to NA)			1.1 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	346 (NA to NA)			1.3 (NA to NA)			1.2 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_offset for Cluster: 4
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	2.6 (-195 to 201)	0.98	0.98	0.57 (-0.15 to 1.3)	0.12	0.48	-0.34 (-1.2 to 0.50)	0.43	0.51	1.2 (0.39 to 2.1)	0.004	0.016
mean_GaitCycleDur	3.2 (-99 to 105)	0.95	0.98	-0.09 (-0.46 to 0.28)	0.65	0.96	-0.12 (-0.49 to 0.25)	0.51	0.51	0.06 (-0.29 to 0.42)	0.73	0.73
group_char		0.036	0.072		0.96	0.96		0.15	0.31		0.17	0.22
H1000’s	—			—			—			—
H2000’s	27 (-320 to 375)			-0.17 (-1.4 to 1.1)			-0.24 (-1.7 to 1.2)			1.2 (-0.20 to 2.7)
H3000’s	-406 (-742 to -70)			-0.12 (-1.3 to 1.1)			1.2 (-0.20 to 2.7)			-0.18 (-1.6 to 1.3)
mean_GaitCycleDur * group_char		0.006	0.024		0.94	0.96		0.085	0.31		0.035	0.070
mean_GaitCycleDur * H2000’s	-18 (-223 to 187)			-0.01 (-0.76 to 0.73)			0.24 (-0.53 to 1.0)			-0.21 (-0.94 to 0.53)
mean_GaitCycleDur * H3000’s	338 (121 to 554)			-0.14 (-0.93 to 0.65)			-0.85 (-1.7 to 0.00)			0.98 (0.17 to 1.8)
subj_char.sd__(Intercept)	25 (NA to NA)			0.14 (NA to NA)			1.1 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	345 (NA to NA)			1.3 (NA to NA)			1.2 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in NA for Cluster: 4
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	6.8 (-155 to 169)	0.93	0.98	0.36 (-0.22 to 0.94)	0.23	0.73	-0.72 (-1.4 to 0.00)	0.050	0.20	1.7 (1.0 to 2.5)	<0.001	<0.001
mean_PeakUpDownVel_mean	7.0 (-608 to 622)	0.98	0.98	0.25 (-2.0 to 2.5)	0.83	0.83	0.66 (-1.6 to 2.9)	0.56	0.56	-1.7 (-3.8 to 0.44)	0.12	0.12
group_char		0.083	0.33		0.37	0.73		0.40	0.53		0.007	0.014
H1000’s	—			—			—			—
H2000’s	-13 (-259 to 234)			-0.54 (-1.4 to 0.34)			0.41 (-0.70 to 1.5)			0.49 (-0.63 to 1.6)
H3000’s	230 (-3.0 to 462)			-0.52 (-1.4 to 0.31)			-0.38 (-1.5 to 0.69)			1.7 (0.62 to 2.8)
mean_PeakUpDownVel_mean * group_char		0.18	0.36		0.67	0.83		0.20	0.41		0.060	0.080
mean_PeakUpDownVel_mean * H2000’s	43 (-847 to 934)			1.4 (-1.8 to 4.6)			-1.0 (-4.2 to 2.2)			1.8 (-1.3 to 4.8)
mean_PeakUpDownVel_mean * H3000’s	-670 (-1,514 to 174)			0.94 (-2.1 to 4.0)			1.9 (-1.3 to 5.1)			-2.0 (-5.0 to 1.0)
subj_char.sd__(Intercept)	32 (NA to NA)			0.09 (NA to NA)			1.1 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	350 (NA to NA)			1.3 (NA to NA)			1.2 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_avg_power for Cluster: 5
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	1.7 (-459 to 462)	0.99	0.99	0.12 (-14 to 14)	0.99	0.99	-0.79 (-2.2 to 0.63)	0.27	0.27	1.7 (0.28 to 3.1)	0.019	0.026
mean_APexc_COV	-0.11 (-27 to 27)	0.99	0.99	0.02 (-0.82 to 0.86)	0.96	0.99	0.05 (-0.04 to 0.13)	0.27	0.27	-0.02 (-0.10 to 0.06)	0.65	0.65
group_char		<0.001	<0.001		0.79	0.99		<0.001	<0.001		<0.001	<0.001
H1000’s	—			—			—			—
H2000’s	-4,333 (-5,151 to -3,516)			4.8 (-19 to 29)			7.4 (4.9 to 9.9)			-6.7 (-9.2 to -4.1)
H3000’s	1.0 (-721 to 723)			7.1 (-13 to 27)			1.1 (-1.1 to 3.3)			-0.94 (-3.2 to 1.3)
mean_APexc_COV * group_char		<0.001	<0.001		0.89	0.99		<0.001	<0.001		<0.001	<0.001
mean_APexc_COV * H2000’s	211 (172 to 250)			-0.29 (-1.5 to 0.91)			-0.40 (-0.52 to -0.28)			0.37 (0.25 to 0.49)
mean_APexc_COV * H3000’s	-0.04 (-33 to 33)			-0.16 (-1.2 to 0.84)			-0.06 (-0.16 to 0.05)			0.05 (-0.05 to 0.15)
subj_char.sd__(Intercept)	368 (NA to NA)			3.5 (NA to NA)			0.99 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	390 (NA to NA)			14 (NA to NA)			1.2 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in alpha_avg_power for Cluster: 5
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-12 (-485 to 461)	0.96	0.99	-0.22 (-11 to 10)	0.97	0.97	-0.47 (-1.7 to 0.73)	0.44	0.80	1.5 (0.27 to 2.7)	0.017	0.068
mean_APexc_mean	223 (-8,190 to 8,637)	0.96	0.99	12 (-175 to 200)	0.90	0.97	8.1 (-13 to 29)	0.45	0.80	-1.8 (-22 to 19)	0.87	0.87
group_char		0.82	0.99		0.025	0.10		0.60	0.80		0.81	0.87
H1000’s	—			—			—			—
H2000’s	254 (-577 to 1,085)			-17 (-36 to 1.8)			-0.88 (-3.0 to 1.3)			-0.01 (-2.2 to 2.2)
H3000’s	18 (-633 to 668)			9.1 (-5.9 to 24)			0.22 (-1.5 to 1.9)			-0.58 (-2.4 to 1.3)
mean_APexc_mean * group_char		0.99	0.99		0.057	0.11		0.99	0.99		0.34	0.67
mean_APexc_mean * H2000’s	94 (-15,874 to 16,063)			328 (-30 to 687)			-1.5 (-42 to 39)			27 (-13 to 66)
mean_APexc_mean * H3000’s	-399 (-14,034 to 13,236)			-152 (-466 to 162)			0.75 (-35 to 37)			19 (-18 to 56)
subj_char.sd__(Intercept)	0.00 (NA to NA)			4.1 (NA to NA)			0.61 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	639 (NA to NA)			14 (NA to NA)			1.5 (NA to NA)			1.4 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_avg_power for Cluster: 5
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	4.5 (-343 to 352)	0.98	0.98	-0.55 (-9.2 to 8.1)	0.90	0.90	-0.22 (-1.2 to 0.80)	0.68	0.90	2.0 (0.93 to 3.2)	<0.001	0.001
mean_MLexc_COV	-0.30 (-22 to 22)	0.98	0.98	0.07 (-0.47 to 0.61)	0.81	0.90	0.01 (-0.05 to 0.07)	0.71	0.90	-0.04 (-0.11 to 0.02)	0.20	0.20
group_char		0.014	0.028		0.38	0.76		0.90	0.90		0.12	0.16
H1000’s	—			—			—			—
H2000’s	-1,170 (-1,973 to -366)			11 (-8.5 to 31)			0.51 (-1.7 to 2.8)			-1.4 (-3.8 to 0.95)
H3000’s	-1.0 (-681 to 679)			-4.7 (-21 to 12)			0.06 (-1.8 to 1.9)			-2.0 (-3.9 to 0.00)
mean_MLexc_COV * group_char		<0.001	0.003		0.18	0.71		0.34	0.90		0.009	0.018
mean_MLexc_COV * H2000’s	102 (48 to 157)			-0.89 (-2.2 to 0.42)			-0.11 (-0.26 to 0.04)			0.19 (0.04 to 0.34)
mean_MLexc_COV * H3000’s	-0.02 (-45 to 45)			0.55 (-0.54 to 1.6)			0.00 (-0.12 to 0.13)			0.15 (0.03 to 0.27)
subj_char.sd__(Intercept)	0.00 (NA to NA)			3.7 (NA to NA)			0.62 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	612 (NA to NA)			14 (NA to NA)			1.5 (NA to NA)			1.4 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_div_theta for Cluster: 5
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-16 (-407 to 374)	0.93	0.93	0.48 (-8.6 to 9.6)	0.92	0.99	-0.01 (-1.1 to 1.0)	0.99	0.99	1.1 (-0.01 to 2.2)	0.051	0.20
mean_MLexc_mean	207 (-4,438 to 4,851)	0.93	0.93	-0.31 (-107 to 107)	0.99	0.99	-0.41 (-13 to 12)	0.95	0.99	3.5 (-8.9 to 16)	0.58	0.61
group_char		0.32	0.93		0.019	0.077		0.40	0.99		0.54	0.61
H1000’s	—			—			—			—
H2000’s	505 (-201 to 1,210)			-16 (-33 to -0.03)			-1.2 (-3.0 to 0.70)			1.0 (-0.96 to 3.0)
H3000’s	16 (-536 to 567)			7.1 (-5.9 to 20)			0.05 (-1.4 to 1.5)			0.70 (-0.94 to 2.3)
mean_MLexc_mean * group_char		0.74	0.93		0.040	0.081		0.99	0.99		0.61	0.61
mean_MLexc_mean * H2000’s	-2,758 (-10,355 to 4,840)			163 (-8.2 to 335)			1.7 (-18 to 21)			2.4 (-17 to 22)
mean_MLexc_mean * H3000’s	-215 (-6,420 to 5,990)			-48 (-191 to 96)			0.81 (-16 to 17)			-6.3 (-23 to 11)
subj_char.sd__(Intercept)	0.00 (NA to NA)			4.7 (NA to NA)			0.60 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	638 (NA to NA)			14 (NA to NA)			1.5 (NA to NA)			1.4 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_div_beta for Cluster: 5
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-6.4 (-396 to 383)	0.97	0.97	-0.07 (-8.7 to 8.6)	0.99	0.99	-0.41 (-1.4 to 0.57)	0.41	0.83	1.3 (0.30 to 2.3)	0.011	0.043
mean_StepDur	7.1 (-402 to 416)	0.97	0.97	0.59 (-8.3 to 9.5)	0.90	0.99	0.42 (-0.58 to 1.4)	0.41	0.83	0.10 (-0.84 to 1.0)	0.83	0.97
group_char		0.23	0.93		0.014	0.050		0.75	0.98		0.97	0.97
H1000’s	—			—			—			—
H2000’s	749 (-132 to 1,630)			-24 (-44 to -4.5)			-0.77 (-3.0 to 1.4)			0.27 (-2.0 to 2.5)
H3000’s	14 (-716 to 745)			8.9 (-7.7 to 26)			0.16 (-1.8 to 2.1)			-0.06 (-2.0 to 1.9)
mean_StepDur * group_char		0.50	0.97		0.025	0.050		0.98	0.98		0.57	0.97
mean_StepDur * H2000’s	-627 (-1,678 to 424)			29 (5.9 to 52)			-0.24 (-2.8 to 2.3)			1.3 (-1.1 to 3.7)
mean_StepDur * H3000’s	-21 (-1,006 to 964)			-8.6 (-31 to 14)			0.09 (-2.4 to 2.6)			0.41 (-2.1 to 2.9)
subj_char.sd__(Intercept)	0.00 (NA to NA)			4.2 (NA to NA)			0.60 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	636 (NA to NA)			14 (NA to NA)			1.5 (NA to NA)			1.4 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_beta_div_theta for Cluster: 5
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-5.7 (-324 to 313)	0.97	0.97	-0.36 (-7.7 to 7.0)	0.92	0.92	-0.43 (-1.3 to 0.40)	0.30	0.46	1.4 (0.52 to 2.3)	0.002	0.007
mean_UDexc_COV	0.44 (-22 to 23)	0.97	0.97	0.06 (-0.45 to 0.58)	0.81	0.92	0.03 (-0.03 to 0.09)	0.29	0.46	0.00 (-0.05 to 0.05)	0.99	0.99
group_char		0.81	0.97		0.13	0.52		0.75	0.75		0.96	0.99
H1000’s	—			—			—			—
H2000’s	-195 (-810 to 421)			-9.3 (-24 to 4.9)			0.03 (-1.6 to 1.6)			-0.22 (-1.9 to 1.5)
H3000’s	8.1 (-579 to 595)			7.7 (-5.8 to 21)			0.56 (-0.95 to 2.1)			0.06 (-1.5 to 1.6)
mean_UDexc_COV * group_char		0.26	0.97		0.26	0.52		0.35	0.46		0.089	0.18
mean_UDexc_COV * H2000’s	32 (-8.8 to 74)			0.56 (-0.38 to 1.5)			-0.08 (-0.18 to 0.03)			0.11 (0.01 to 0.21)
mean_UDexc_COV * H3000’s	-0.69 (-40 to 39)			-0.33 (-1.2 to 0.56)			-0.03 (-0.13 to 0.06)			0.01 (-0.08 to 0.10)
subj_char.sd__(Intercept)	0.00 (NA to NA)			3.5 (NA to NA)			0.59 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	633 (NA to NA)			14 (NA to NA)			1.5 (NA to NA)			1.4 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_theta_div_beta for Cluster: 5
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	7.6 (-362 to 377)	0.97	0.97	0.60 (-7.8 to 9.0)	0.89	0.97	0.26 (-0.70 to 1.2)	0.60	0.60	1.3 (0.28 to 2.3)	0.012	0.033
mean_UDexc_mean	-316 (-14,912 to 14,279)	0.97	0.97	-6.0 (-333 to 321)	0.97	0.97	-12 (-49 to 24)	0.51	0.60	5.3 (-30 to 41)	0.77	0.77
group_char		0.062	0.25		0.14	0.27		0.045	0.18		0.016	0.033
H1000’s	—			—			—			—
H2000’s	846 (100 to 1,593)			16 (-0.82 to 33)			-2.4 (-4.4 to -0.49)			2.8 (0.79 to 4.8)
H3000’s	-11 (-580 to 558)			-0.57 (-14 to 12)			-0.32 (-1.8 to 1.2)			0.01 (-1.6 to 1.6)
mean_UDexc_mean * group_char		0.22	0.43		0.035	0.14		0.29	0.57		0.15	0.20
mean_UDexc_mean * H2000’s	-24,211 (-53,231 to 4,808)			-727 (-1,380 to -73)			59 (-14 to 132)			-64 (-135 to 7.7)
mean_UDexc_mean * H3000’s	411 (-21,507 to 22,329)			149 (-346 to 644)			19 (-37 to 74)			7.1 (-47 to 61)
subj_char.sd__(Intercept)	0.00 (NA to NA)			3.7 (NA to NA)			0.60 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	633 (NA to NA)			14 (NA to NA)			1.5 (NA to NA)			1.4 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_exp for Cluster: 5
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-4.6 (-333 to 324)	0.98	0.98	0.03 (-7.3 to 7.3)	0.99	0.99	-0.38 (-1.2 to 0.46)	0.38	0.75	1.3 (0.44 to 2.2)	0.003	0.013
mean_StanceDur	3.8 (-244 to 251)	0.98	0.98	0.35 (-5.0 to 5.7)	0.90	0.99	0.28 (-0.33 to 0.88)	0.37	0.75	0.07 (-0.50 to 0.64)	0.82	0.85
group_char		0.26	0.98		0.012	0.044		0.68	0.91		0.85	0.85
H1000’s	—			—			—			—
H2000’s	579 (-127 to 1,285)			-19 (-35 to -3.4)			-0.68 (-2.5 to 1.1)			0.52 (-1.3 to 2.4)
H3000’s	10 (-600 to 621)			8.0 (-5.8 to 22)			0.22 (-1.4 to 1.8)			0.00 (-1.7 to 1.7)
mean_StanceDur * group_char		0.61	0.98		0.022	0.044		0.94	0.94		0.60	0.85
mean_StanceDur * H2000’s	-299 (-896 to 299)			16 (3.5 to 29)			-0.27 (-1.7 to 1.2)			0.71 (-0.67 to 2.1)
mean_StanceDur * H3000’s	-12 (-602 to 579)			-5.3 (-18 to 7.9)			-0.01 (-1.5 to 1.5)			0.23 (-1.2 to 1.7)
subj_char.sd__(Intercept)	0.00 (NA to NA)			4.2 (NA to NA)			0.60 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	637 (NA to NA)			14 (NA to NA)			1.5 (NA to NA)			1.4 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_offset for Cluster: 5
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-6.4 (-396 to 383)	0.97	0.97	-0.08 (-8.7 to 8.6)	0.99	0.99	-0.41 (-1.4 to 0.57)	0.41	0.83	1.3 (0.30 to 2.3)	0.011	0.043
mean_GaitCycleDur	3.6 (-201 to 208)	0.97	0.97	0.30 (-4.2 to 4.7)	0.90	0.99	0.21 (-0.29 to 0.71)	0.42	0.83	0.05 (-0.42 to 0.52)	0.83	0.97
group_char		0.24	0.95		0.014	0.050		0.75	0.98		0.97	0.97
H1000’s	—			—			—			—
H2000’s	743 (-137 to 1,623)			-24 (-43 to -4.4)			-0.77 (-3.0 to 1.4)			0.25 (-2.0 to 2.5)
H3000’s	14 (-716 to 745)			8.9 (-7.7 to 26)			0.16 (-1.7 to 2.1)			-0.06 (-2.0 to 1.9)
mean_GaitCycleDur * group_char		0.51	0.97		0.025	0.050		0.98	0.98		0.56	0.97
mean_GaitCycleDur * H2000’s	-309 (-834 to 215)			14 (2.9 to 26)			-0.12 (-1.4 to 1.2)			0.66 (-0.56 to 1.9)
mean_GaitCycleDur * H3000’s	-11 (-503 to 482)			-4.3 (-15 to 6.8)			0.05 (-1.2 to 1.3)			0.20 (-1.1 to 1.5)
subj_char.sd__(Intercept)	0.00 (NA to NA)			4.2 (NA to NA)			0.60 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	636 (NA to NA)			14 (NA to NA)			1.5 (NA to NA)			1.4 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in NA for Cluster: 5
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	8.3 (-297 to 313)	0.96	0.96	0.73 (-6.1 to 7.6)	0.84	0.93	0.16 (-0.62 to 0.95)	0.68	0.68	1.4 (0.62 to 2.3)	<0.001	0.002
mean_PeakUpDownVel_mean	-35 (-1,205 to 1,135)	0.95	0.96	-1.2 (-27 to 25)	0.93	0.93	-0.85 (-3.7 to 2.0)	0.56	0.68	-0.22 (-2.9 to 2.5)	0.87	0.87
group_char		0.18	0.74		0.18	0.35		0.076	0.30		0.021	0.041
H1000’s	—			—			—			—
H2000’s	553 (-70 to 1,177)			13 (-0.87 to 27)			-1.8 (-3.4 to -0.22)			2.2 (0.53 to 3.9)
H3000’s	-12 (-510 to 486)			1.5 (-9.8 to 13)			-0.16 (-1.4 to 1.1)			-0.19 (-1.6 to 1.2)
mean_PeakUpDownVel_mean * group_char		0.55	0.96		0.042	0.17		0.52	0.68		0.20	0.26
mean_PeakUpDownVel_mean * H2000’s	-1,162 (-3,440 to 1,115)			-57 (-108 to -7.3)			3.3 (-2.3 to 8.9)			-3.7 (-9.0 to 1.6)
mean_PeakUpDownVel_mean * H3000’s	45 (-1,689 to 1,778)			5.7 (-33 to 44)			1.1 (-3.2 to 5.4)			1.4 (-2.7 to 5.5)
subj_char.sd__(Intercept)	0.00 (NA to NA)			3.6 (NA to NA)			0.60 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	636 (NA to NA)			14 (NA to NA)			1.5 (NA to NA)			1.4 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_avg_power for Cluster: 6
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-0.68 (-9.6 to 8.2)	0.88	0.88	7.2 (-0.74 to 15)	0.075	0.30	-0.59 (-1.2 to 0.03)	0.061	0.25	0.12 (-0.51 to 0.75)	0.71	0.71
mean_APexc_COV	0.16 (-0.38 to 0.70)	0.56	0.74	-0.17 (-0.65 to 0.30)	0.47	0.63	0.01 (-0.02 to 0.05)	0.52	0.77	0.02 (-0.01 to 0.05)	0.12	0.30
group_char		0.083	0.33		0.45	0.63		0.60	0.77		0.15	0.30
H1000’s	—			—			—			—
H2000’s	-8.2 (-22 to 5.5)			-7.2 (-20 to 5.1)			0.48 (-0.49 to 1.5)			0.87 (-0.13 to 1.9)
H3000’s	7.7 (-5.2 to 21)			-6.0 (-18 to 5.8)			0.06 (-0.89 to 1.0)			0.77 (-0.21 to 1.8)
mean_APexc_COV * group_char		0.20	0.40		0.74	0.74		0.77	0.77		0.37	0.50
mean_APexc_COV * H2000’s	0.17 (-0.53 to 0.86)			0.25 (-0.37 to 0.86)			-0.01 (-0.06 to 0.03)			-0.02 (-0.06 to 0.02)
mean_APexc_COV * H3000’s	-0.34 (-0.98 to 0.31)			0.15 (-0.43 to 0.73)			0.00 (-0.04 to 0.05)			-0.03 (-0.07 to 0.01)
subj_char.sd__(Intercept)	0.00 (NA to NA)			3.6 (NA to NA)			0.47 (NA to NA)			0.99 (NA to NA)
Residual.sd__Observation	11 (NA to NA)			8.6 (NA to NA)			0.61 (NA to NA)			0.48 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in alpha_avg_power for Cluster: 6
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	1.8 (-5.8 to 9.5)	0.64	0.98	3.3 (-3.3 to 9.9)	0.32	0.96	-0.23 (-0.74 to 0.28)	0.38	0.87	0.44 (-0.10 to 0.99)	0.11	0.45
mean_APexc_mean	2.0 (-134 to 138)	0.98	0.98	20 (-96 to 136)	0.73	0.96	-3.2 (-12 to 5.3)	0.46	0.87	1.3 (-5.7 to 8.3)	0.72	0.89
group_char		0.75	0.98		0.86	0.96		0.96	0.96		0.39	0.79
H1000’s	—			—			—			—
H2000’s	-1.4 (-12 to 9.5)			-1.8 (-11 to 7.8)			-0.07 (-0.82 to 0.69)			0.59 (-0.26 to 1.4)
H3000’s	2.3 (-7.5 to 12)			-2.4 (-11 to 6.3)			0.05 (-0.65 to 0.75)			0.28 (-0.51 to 1.1)
mean_APexc_mean * group_char		0.89	0.98		0.96	0.96		0.65	0.87		0.89	0.89
mean_APexc_mean * H2000’s	-43 (-255 to 168)			-17 (-200 to 167)			6.5 (-7.3 to 20)			-1.5 (-13 to 10)
mean_APexc_mean * H3000’s	-40 (-237 to 156)			-26 (-198 to 147)			2.3 (-11 to 15)			1.6 (-9.7 to 13)
subj_char.sd__(Intercept)	0.00 (NA to NA)			3.5 (NA to NA)			0.48 (NA to NA)			0.98 (NA to NA)
Residual.sd__Observation	11 (NA to NA)			8.6 (NA to NA)			0.61 (NA to NA)			0.49 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_avg_power for Cluster: 6
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	3.9 (-2.1 to 10)	0.20	0.27	3.5 (-2.3 to 9.3)	0.24	0.60	-0.61 (-1.1 to -0.12)	0.015	0.060	0.67 (0.09 to 1.2)	0.022	0.089
mean_MLexc_COV	-0.14 (-0.53 to 0.25)	0.48	0.48	0.06 (-0.31 to 0.44)	0.75	0.75	0.01 (-0.02 to 0.04)	0.36	0.36	-0.01 (-0.04 to 0.02)	0.47	0.54
group_char		<0.001	0.004		0.33	0.60		0.039	0.078		0.38	0.54
H1000’s	—			—			—			—
H2000’s	-14 (-23 to -4.2)			-6.7 (-16 to 2.2)			0.85 (0.12 to 1.6)			0.58 (-0.28 to 1.4)
H3000’s	5.6 (-4.3 to 15)			-2.2 (-11 to 6.9)			-0.01 (-0.75 to 0.74)			0.08 (-0.77 to 0.93)
mean_MLexc_COV * group_char		0.009	0.017		0.45	0.60		0.061	0.081		0.54	0.54
mean_MLexc_COV * H2000’s	0.73 (0.10 to 1.4)			0.28 (-0.29 to 0.86)			-0.04 (-0.09 to 0.00)			-0.01 (-0.05 to 0.04)
mean_MLexc_COV * H3000’s	-0.35 (-1.0 to 0.31)			-0.11 (-0.71 to 0.49)			0.01 (-0.03 to 0.06)			0.02 (-0.02 to 0.06)
subj_char.sd__(Intercept)	0.00 (NA to NA)			3.4 (NA to NA)			0.45 (NA to NA)			0.98 (NA to NA)
Residual.sd__Observation	10 (NA to NA)			8.6 (NA to NA)			0.61 (NA to NA)			0.48 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_div_theta for Cluster: 6
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	0.39 (-5.9 to 6.7)	0.90	0.92	5.3 (-0.38 to 11)	0.067	0.27	-0.18 (-0.64 to 0.27)	0.43	0.86	0.33 (-0.19 to 0.86)	0.21	0.40
mean_MLexc_mean	19 (-55 to 92)	0.62	0.92	-11 (-76 to 53)	0.73	0.97	-2.7 (-7.6 to 2.2)	0.28	0.86	2.2 (-1.9 to 6.4)	0.30	0.40
group_char		0.92	0.92		0.52	0.97		0.98	0.98		0.30	0.40
H1000’s	—			—			—			—
H2000’s	1.2 (-7.8 to 10)			-3.7 (-12 to 4.5)			0.05 (-0.60 to 0.71)			0.59 (-0.19 to 1.4)
H3000’s	1.7 (-6.8 to 10)			-4.3 (-12 to 3.5)			0.00 (-0.64 to 0.63)			0.42 (-0.34 to 1.2)
mean_MLexc_mean * group_char		0.54	0.92		0.97	0.97		0.72	0.95		0.89	0.89
mean_MLexc_mean * H2000’s	-52 (-151 to 46)			12 (-74 to 98)			2.5 (-4.0 to 9.0)			-1.2 (-6.7 to 4.3)
mean_MLexc_mean * H3000’s	-13 (-108 to 83)			7.1 (-78 to 92)			2.3 (-4.2 to 8.8)			-1.2 (-6.7 to 4.3)
subj_char.sd__(Intercept)	0.00 (NA to NA)			3.6 (NA to NA)			0.47 (NA to NA)			0.98 (NA to NA)
Residual.sd__Observation	11 (NA to NA)			8.6 (NA to NA)			0.61 (NA to NA)			0.48 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_div_beta for Cluster: 6
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	1.2 (-7.3 to 9.7)	0.78	0.86	7.5 (2.2 to 13)	0.006	0.022	-0.36 (-0.80 to 0.07)	0.10	0.41	0.54 (0.05 to 1.0)	0.030	0.12
mean_StepDur	0.81 (-7.9 to 9.5)	0.86	0.86	-3.4 (-8.6 to 1.9)	0.21	0.42	-0.04 (-0.45 to 0.36)	0.83	0.83	-0.03 (-0.34 to 0.27)	0.84	0.90
group_char		0.32	0.64		0.32	0.43		0.53	0.72		0.90	0.90
H1000’s	—			—			—			—
H2000’s	6.6 (-9.0 to 22)			-5.2 (-15 to 4.6)			0.14 (-0.66 to 0.94)			0.19 (-0.65 to 1.0)
H3000’s	-7.0 (-22 to 7.6)			-6.4 (-16 to 2.9)			0.45 (-0.33 to 1.2)			0.13 (-0.68 to 0.94)
mean_StepDur * group_char		0.073	0.29		0.84	0.84		0.54	0.72		0.41	0.82
mean_StepDur * H2000’s	-13 (-32 to 5.8)			2.6 (-9.0 to 14)			0.14 (-0.75 to 1.0)			0.42 (-0.27 to 1.1)
mean_StepDur * H3000’s	15 (-4.3 to 34)			2.8 (-9.1 to 15)			-0.48 (-1.4 to 0.47)			0.31 (-0.44 to 1.1)
subj_char.sd__(Intercept)	3.0 (NA to NA)			3.6 (NA to NA)			0.51 (NA to NA)			1.0 (NA to NA)
Residual.sd__Observation	14 (NA to NA)			8.5 (NA to NA)			0.64 (NA to NA)			0.49 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_beta_div_theta for Cluster: 6
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	0.62 (-5.0 to 6.2)	0.83	0.95	6.3 (1.5 to 11)	0.011	0.042	-0.28 (-0.66 to 0.11)	0.16	0.65	0.52 (0.04 to 0.99)	0.033	0.13
mean_UDexc_COV	0.11 (-0.31 to 0.53)	0.62	0.95	-0.16 (-0.51 to 0.20)	0.39	0.51	-0.01 (-0.04 to 0.02)	0.43	0.86	0.00 (-0.02 to 0.02)	0.98	0.98
group_char		0.59	0.95		0.29	0.51		0.95	0.95		0.43	0.87
H1000’s	—			—			—			—
H2000’s	-2.9 (-11 to 5.5)			-4.8 (-12 to 2.6)			0.09 (-0.50 to 0.68)			0.47 (-0.28 to 1.2)
H3000’s	2.0 (-7.0 to 11)			-5.5 (-13 to 2.3)			0.00 (-0.62 to 0.62)			0.33 (-0.41 to 1.1)
mean_UDexc_COV * group_char		0.95	0.95		0.78	0.78		0.71	0.94		0.98	0.98
mean_UDexc_COV * H2000’s	-0.05 (-0.64 to 0.54)			0.16 (-0.33 to 0.66)			0.01 (-0.02 to 0.05)			0.00 (-0.03 to 0.03)
mean_UDexc_COV * H3000’s	-0.10 (-0.75 to 0.54)			0.14 (-0.40 to 0.69)			0.01 (-0.03 to 0.05)			0.00 (-0.03 to 0.03)
subj_char.sd__(Intercept)	0.00 (NA to NA)			3.6 (NA to NA)			0.47 (NA to NA)			0.99 (NA to NA)
Residual.sd__Observation	11 (NA to NA)			8.6 (NA to NA)			0.61 (NA to NA)			0.49 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_theta_div_beta for Cluster: 6
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	3.3 (-2.9 to 9.4)	0.30	0.40	2.8 (-2.6 to 8.1)	0.31	0.87	-0.58 (-1.0 to -0.16)	0.007	0.027	0.54 (0.05 to 1.0)	0.032	0.13
mean_UDexc_mean	-58 (-306 to 191)	0.65	0.65	70 (-140 to 280)	0.51	0.87	7.5 (-7.7 to 23)	0.33	0.45	-0.90 (-13 to 12)	0.89	0.89
group_char		0.011	0.045		0.81	0.87		0.21	0.43		0.22	0.44
H1000’s	—			—			—			—
H2000’s	-10 (-20 to -1.1)			-2.5 (-11 to 5.6)			0.57 (-0.07 to 1.2)			0.68 (-0.09 to 1.5)
H3000’s	3.8 (-5.2 to 13)			-2.0 (-9.9 to 6.0)			0.24 (-0.39 to 0.87)			0.21 (-0.54 to 0.95)
mean_UDexc_mean * group_char		0.075	0.15		0.87	0.87		0.47	0.47		0.46	0.61
mean_UDexc_mean * H2000’s	292 (-72 to 656)			-10 (-319 to 299)			-14 (-36 to 9.0)			-7.2 (-26 to 11)
mean_UDexc_mean * H3000’s	-128 (-485 to 229)			-76 (-381 to 229)			-2.5 (-25 to 20)			5.0 (-13 to 24)
subj_char.sd__(Intercept)	0.00 (NA to NA)			3.5 (NA to NA)			0.47 (NA to NA)			0.98 (NA to NA)
Residual.sd__Observation	10 (NA to NA)			8.6 (NA to NA)			0.61 (NA to NA)			0.49 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_exp for Cluster: 6
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	1.1 (-5.9 to 8.2)	0.75	0.81	7.1 (2.6 to 12)	0.002	0.008	-0.36 (-0.74 to 0.02)	0.062	0.25	0.53 (0.07 to 1.0)	0.024	0.095
mean_StanceDur	0.62 (-4.5 to 5.8)	0.81	0.81	-2.1 (-5.3 to 1.0)	0.18	0.32	-0.03 (-0.27 to 0.21)	0.79	0.79	-0.02 (-0.20 to 0.17)	0.87	0.87
group_char		0.45	0.81		0.24	0.32		0.56	0.79		0.76	0.87
H1000’s	—			—			—			—
H2000’s	3.9 (-9.1 to 17)			-4.9 (-13 to 3.3)			0.17 (-0.51 to 0.85)			0.28 (-0.50 to 1.1)
H3000’s	-5.5 (-18 to 6.8)			-6.1 (-14 to 1.7)			0.36 (-0.30 to 1.0)			0.17 (-0.58 to 0.92)
mean_StanceDur * group_char		0.088	0.35		0.83	0.83		0.60	0.79		0.47	0.87
mean_StanceDur * H2000’s	-7.0 (-18 to 4.4)			1.6 (-5.3 to 8.6)			0.07 (-0.46 to 0.61)			0.22 (-0.19 to 0.62)
mean_StanceDur * H3000’s	9.2 (-2.4 to 21)			1.8 (-5.4 to 8.9)			-0.26 (-0.82 to 0.30)			0.18 (-0.25 to 0.62)
subj_char.sd__(Intercept)	3.1 (NA to NA)			3.6 (NA to NA)			0.51 (NA to NA)			1.0 (NA to NA)
Residual.sd__Observation	14 (NA to NA)			8.5 (NA to NA)			0.64 (NA to NA)			0.49 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_offset for Cluster: 6
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	1.2 (-7.3 to 9.7)	0.78	0.86	7.5 (2.2 to 13)	0.006	0.022	-0.36 (-0.80 to 0.07)	0.10	0.41	0.54 (0.05 to 1.0)	0.030	0.12
mean_GaitCycleDur	0.40 (-3.9 to 4.7)	0.86	0.86	-1.7 (-4.3 to 0.96)	0.21	0.43	-0.02 (-0.22 to 0.18)	0.83	0.83	-0.02 (-0.17 to 0.14)	0.84	0.89
group_char		0.32	0.64		0.32	0.43		0.53	0.72		0.89	0.89
H1000’s	—			—			—			—
H2000’s	6.5 (-9.1 to 22)			-5.2 (-15 to 4.5)			0.14 (-0.66 to 0.94)			0.19 (-0.65 to 1.0)
H3000’s	-7.1 (-22 to 7.6)			-6.4 (-16 to 2.9)			0.44 (-0.33 to 1.2)			0.13 (-0.68 to 0.95)
mean_GaitCycleDur * group_char		0.073	0.29		0.84	0.84		0.54	0.72		0.42	0.84
mean_GaitCycleDur * H2000’s	-6.5 (-16 to 2.9)			1.3 (-4.5 to 7.1)			0.07 (-0.37 to 0.52)			0.21 (-0.14 to 0.55)
mean_GaitCycleDur * H3000’s	7.4 (-2.1 to 17)			1.4 (-4.6 to 7.4)			-0.24 (-0.71 to 0.24)			0.15 (-0.22 to 0.52)
subj_char.sd__(Intercept)	3.0 (NA to NA)			3.6 (NA to NA)			0.51 (NA to NA)			1.0 (NA to NA)
Residual.sd__Observation	14 (NA to NA)			8.5 (NA to NA)			0.64 (NA to NA)			0.49 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in NA for Cluster: 6
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	2.8 (-2.2 to 7.7)	0.28	0.37	2.8 (-1.5 to 7.2)	0.20	0.81	-0.49 (-0.84 to -0.15)	0.005	0.021	0.52 (0.07 to 0.97)	0.024	0.10
mean_PeakUpDownVel_mean	-3.6 (-23 to 16)	0.72	0.72	6.8 (-9.4 to 23)	0.41	0.82	0.40 (-0.77 to 1.6)	0.50	0.63	-0.03 (-0.96 to 0.90)	0.95	0.95
group_char		0.010	0.041		0.76	0.85		0.27	0.53		0.21	0.41
H1000’s	—			—			—			—
H2000’s	-8.9 (-17 to -1.1)			-2.1 (-8.9 to 4.7)			0.45 (-0.10 to 1.0)			0.65 (-0.07 to 1.4)
H3000’s	3.5 (-4.1 to 11)			-2.2 (-8.9 to 4.4)			0.22 (-0.32 to 0.76)			0.30 (-0.39 to 1.0)
mean_PeakUpDownVel_mean * group_char		0.085	0.17		0.85	0.85		0.63	0.63		0.61	0.82
mean_PeakUpDownVel_mean * H2000’s	22 (-6.8 to 50)			-3.2 (-27 to 20)			-0.81 (-2.5 to 0.89)			-0.55 (-1.9 to 0.82)
mean_PeakUpDownVel_mean * H3000’s	-9.5 (-37 to 18)			-6.7 (-29 to 16)			-0.19 (-1.8 to 1.5)			0.10 (-1.2 to 1.4)
subj_char.sd__(Intercept)	0.00 (NA to NA)			3.5 (NA to NA)			0.47 (NA to NA)			0.99 (NA to NA)
Residual.sd__Observation	10 (NA to NA)			8.6 (NA to NA)			0.61 (NA to NA)			0.49 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_avg_power for Cluster: 7
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-11 (-54 to 33)	0.64	0.94	1.0 (-1.3 to 3.3)	0.38	0.89	-0.65 (-1.7 to 0.37)	0.21	0.84	2.2 (0.97 to 3.5)	<0.001	0.002
mean_APexc_COV	-0.10 (-2.8 to 2.6)	0.94	0.94	-0.04 (-0.18 to 0.10)	0.58	0.89	0.00 (-0.06 to 0.06)	0.90	0.90	-0.02 (-0.09 to 0.05)	0.59	0.59
group_char		0.81	0.94		0.85	0.89		0.48	0.90		0.13	0.19
H1000’s	—			—			—			—
H2000’s	-18 (-95 to 58)			-1.1 (-5.2 to 2.9)			0.28 (-1.6 to 2.2)			1.7 (-0.68 to 4.2)
H3000’s	6.0 (-52 to 64)			-0.62 (-3.7 to 2.5)			0.86 (-0.54 to 2.3)			-0.75 (-2.5 to 0.99)
mean_APexc_COV * group_char		0.70	0.94		0.89	0.89		0.83	0.90		0.14	0.19
mean_APexc_COV * H2000’s	1.4 (-2.5 to 5.2)			0.05 (-0.15 to 0.25)			-0.02 (-0.11 to 0.07)			-0.04 (-0.15 to 0.07)
mean_APexc_COV * H3000’s	0.07 (-3.0 to 3.1)			0.03 (-0.13 to 0.19)			-0.02 (-0.09 to 0.05)			0.05 (-0.03 to 0.13)
subj_char.sd__(Intercept)	17 (NA to NA)			1.2 (NA to NA)			0.84 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	50 (NA to NA)			2.5 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in alpha_avg_power for Cluster: 7
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-17 (-53 to 20)	0.37	0.83	1.6 (-0.26 to 3.5)	0.091	0.34	-0.59 (-1.4 to 0.24)	0.16	0.34	1.6 (0.60 to 2.7)	0.002	0.008
mean_APexc_mean	79 (-551 to 709)	0.81	0.83	-22 (-54 to 9.6)	0.17	0.34	0.03 (-13 to 14)	0.99	0.99	5.1 (-11 to 21)	0.53	0.89
group_char		0.83	0.83		0.47	0.63		0.17	0.34		0.75	0.89
H1000’s	—			—			—			—
H2000’s	5.3 (-48 to 59)			-1.3 (-4.1 to 1.4)			-0.51 (-1.8 to 0.75)			0.54 (-1.0 to 2.1)
H3000’s	-9.6 (-57 to 38)			-1.5 (-3.9 to 1.0)			0.64 (-0.48 to 1.8)			0.47 (-0.96 to 1.9)
mean_APexc_mean * group_char		0.67	0.83		0.63	0.63		0.42	0.56		0.89	0.89
mean_APexc_mean * H2000’s	141 (-873 to 1,156)			18 (-34 to 70)			9.1 (-13 to 31)			5.0 (-21 to 31)
mean_APexc_mean * H3000’s	422 (-511 to 1,356)			22 (-26 to 70)			-6.9 (-28 to 14)			-1.7 (-27 to 23)
subj_char.sd__(Intercept)	16 (NA to NA)			1.2 (NA to NA)			0.82 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	50 (NA to NA)			2.5 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_avg_power for Cluster: 7
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-8.2 (-44 to 27)	0.65	0.82	0.66 (-1.2 to 2.5)	0.49	0.88	-0.07 (-0.95 to 0.82)	0.88	0.88	1.8 (0.65 to 2.9)	0.002	0.008
mean_MLexc_COV	-0.29 (-2.7 to 2.2)	0.82	0.82	-0.02 (-0.15 to 0.11)	0.76	0.88	-0.04 (-0.10 to 0.02)	0.20	0.81	0.01 (-0.06 to 0.08)	0.79	0.79
group_char		0.46	0.82		0.78	0.88		0.42	0.83		0.045	0.090
H1000’s	—			—			—			—
H2000’s	19 (-33 to 71)			-0.98 (-3.7 to 1.8)			-0.60 (-1.9 to 0.68)			2.1 (0.44 to 3.7)
H3000’s	-14 (-64 to 36)			-0.59 (-3.2 to 2.0)			0.23 (-0.99 to 1.5)			0.87 (-0.67 to 2.4)
mean_MLexc_COV * group_char		0.48	0.82		0.88	0.88		0.64	0.85		0.16	0.21
mean_MLexc_COV * H2000’s	-0.54 (-4.0 to 2.9)			0.05 (-0.13 to 0.23)			0.04 (-0.04 to 0.12)			-0.10 (-0.19 to 0.00)
mean_MLexc_COV * H3000’s	1.5 (-1.9 to 4.9)			0.02 (-0.15 to 0.20)			0.01 (-0.07 to 0.09)			-0.04 (-0.13 to 0.06)
subj_char.sd__(Intercept)	17 (NA to NA)			1.2 (NA to NA)			0.83 (NA to NA)			1.3 (NA to NA)
Residual.sd__Observation	50 (NA to NA)			2.5 (NA to NA)			1.0 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_div_theta for Cluster: 7
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-31 (-63 to 1.8)	0.064	0.26	1.3 (-0.39 to 3.0)	0.13	0.51	-0.77 (-1.5 to 0.00)	0.049	0.20	1.8 (0.87 to 2.8)	<0.001	<0.001
mean_MLexc_mean	222 (-143 to 586)	0.23	0.47	-11 (-30 to 7.8)	0.25	0.51	2.2 (-5.9 to 10)	0.60	0.67	0.82 (-8.6 to 10)	0.87	0.88
group_char		0.69	0.90		0.58	0.69		0.27	0.54		0.88	0.88
H1000’s	—			—			—			—
H2000’s	20 (-26 to 66)			-1.0 (-3.4 to 1.4)			-0.30 (-1.4 to 0.81)			0.34 (-1.1 to 1.8)
H3000’s	13 (-30 to 55)			-1.1 (-3.3 to 1.1)			0.54 (-0.48 to 1.6)			0.28 (-1.0 to 1.6)
mean_MLexc_mean * group_char		0.90	0.90		0.69	0.69		0.67	0.67		0.75	0.88
mean_MLexc_mean * H2000’s	-111 (-596 to 374)			8.6 (-16 to 33)			2.2 (-8.5 to 13)			4.3 (-8.3 to 17)
mean_MLexc_mean * H3000’s	-73 (-544 to 398)			10 (-14 to 35)			-2.3 (-13 to 8.2)			0.58 (-12 to 13)
subj_char.sd__(Intercept)	16 (NA to NA)			1.2 (NA to NA)			0.82 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	50 (NA to NA)			2.5 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_div_beta for Cluster: 7
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-20 (-50 to 9.3)	0.18	0.72	1.2 (-0.27 to 2.8)	0.11	0.43	-0.43 (-1.1 to 0.25)	0.22	0.58	1.7 (0.80 to 2.5)	<0.001	<0.001
mean_StepDur	8.9 (-21 to 39)	0.56	0.97	-0.94 (-2.4 to 0.56)	0.22	0.44	-0.18 (-0.80 to 0.44)	0.58	0.58	0.27 (-0.44 to 0.99)	0.45	0.85
group_char		0.97	0.97		0.66	0.83		0.32	0.58		0.85	0.85
H1000’s	—			—			—			—
H2000’s	1.1 (-53 to 55)			-0.88 (-3.6 to 1.9)			-0.76 (-2.0 to 0.45)			0.41 (-1.1 to 1.9)
H3000’s	-5.3 (-54 to 44)			-1.1 (-3.6 to 1.4)			0.24 (-0.88 to 1.4)			0.28 (-1.1 to 1.7)
mean_StepDur * group_char		0.78	0.97		0.83	0.83		0.44	0.58		0.83	0.85
mean_StepDur * H2000’s	14 (-48 to 76)			0.56 (-2.5 to 3.7)			0.84 (-0.45 to 2.1)			0.46 (-1.0 to 2.0)
mean_StepDur * H3000’s	20 (-42 to 82)			0.90 (-2.2 to 4.0)			0.12 (-1.2 to 1.4)			0.16 (-1.4 to 1.7)
subj_char.sd__(Intercept)	17 (NA to NA)			1.2 (NA to NA)			0.83 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	49 (NA to NA)			2.5 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_beta_div_theta for Cluster: 7
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-19 (-45 to 7.2)	0.16	0.63	1.2 (-0.09 to 2.6)	0.067	0.27	-0.67 (-1.3 to -0.06)	0.033	0.13	1.8 (1.0 to 2.6)	<0.001	<0.001
mean_UDexc_COV	0.52 (-1.3 to 2.4)	0.58	0.99	-0.07 (-0.16 to 0.02)	0.15	0.30	0.01 (-0.03 to 0.05)	0.73	0.91	0.01 (-0.04 to 0.05)	0.76	0.98
group_char		0.99	0.99		0.48	0.57		0.79	0.91		0.57	0.98
H1000’s	—			—			—			—
H2000’s	2.4 (-38 to 42)			-1.1 (-3.1 to 1.0)			-0.19 (-1.2 to 0.77)			0.69 (-0.59 to 2.0)
H3000’s	3.1 (-37 to 43)			-1.1 (-3.2 to 0.97)			0.17 (-0.78 to 1.1)			0.36 (-0.87 to 1.6)
mean_UDexc_COV * group_char		0.90	0.99		0.57	0.57		0.91	0.91		0.98	0.98
mean_UDexc_COV * H2000’s	0.65 (-2.1 to 3.4)			0.06 (-0.08 to 0.20)			0.01 (-0.05 to 0.07)			0.00 (-0.07 to 0.07)
mean_UDexc_COV * H3000’s	0.21 (-2.5 to 3.0)			0.07 (-0.07 to 0.21)			0.01 (-0.05 to 0.07)			0.00 (-0.07 to 0.07)
subj_char.sd__(Intercept)	16 (NA to NA)			1.2 (NA to NA)			0.83 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	50 (NA to NA)			2.5 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_theta_div_beta for Cluster: 7
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-14 (-44 to 15)	0.34	0.87	-0.48 (-2.0 to 1.0)	0.53	0.84	-0.67 (-1.3 to 0.01)	0.053	0.21	2.3 (1.4 to 3.1)	<0.001	<0.001
mean_UDexc_mean	91 (-1,037 to 1,219)	0.87	0.87	36 (-20 to 93)	0.21	0.83	3.5 (-20 to 27)	0.77	0.87	-15 (-42 to 13)	0.30	0.60
group_char		0.46	0.87		0.84	0.84		0.56	0.87		0.65	0.86
H1000’s	—			—			—			—
H2000’s	28 (-18 to 73)			0.34 (-2.0 to 2.7)			0.14 (-0.94 to 1.2)			0.66 (-0.73 to 2.0)
H3000’s	18 (-23 to 60)			0.65 (-1.5 to 2.8)			0.53 (-0.45 to 1.5)			0.22 (-1.0 to 1.5)
mean_UDexc_mean * group_char		0.72	0.87		0.63	0.84		0.87	0.87		0.97	0.97
mean_UDexc_mean * H2000’s	-684 (-2,430 to 1,061)			-28 (-116 to 60)			-9.2 (-46 to 28)			3.3 (-40 to 46)
mean_UDexc_mean * H3000’s	-464 (-2,041 to 1,112)			-38 (-117 to 42)			-7.2 (-41 to 27)			4.8 (-35 to 44)
subj_char.sd__(Intercept)	16 (NA to NA)			1.2 (NA to NA)			0.83 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	50 (NA to NA)			2.5 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_exp for Cluster: 7
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-18 (-43 to 6.7)	0.15	0.61	1.1 (-0.16 to 2.4)	0.087	0.35	-0.45 (-1.0 to 0.14)	0.14	0.48	1.7 (0.93 to 2.5)	<0.001	<0.001
mean_StanceDur	4.9 (-13 to 23)	0.59	0.94	-0.59 (-1.5 to 0.30)	0.19	0.39	-0.11 (-0.48 to 0.25)	0.55	0.55	0.17 (-0.26 to 0.59)	0.44	0.89
group_char		0.94	0.94		0.63	0.83		0.24	0.48		0.69	0.92
H1000’s	—			—			—			—
H2000’s	3.7 (-41 to 49)			-0.83 (-3.1 to 1.5)			-0.68 (-1.7 to 0.35)			0.58 (-0.76 to 1.9)
H3000’s	-5.3 (-46 to 36)			-0.93 (-3.0 to 1.2)			0.28 (-0.67 to 1.2)			0.29 (-0.94 to 1.5)
mean_StanceDur * group_char		0.73	0.94		0.83	0.83		0.37	0.49		0.92	0.92
mean_StanceDur * H2000’s	8.0 (-29 to 45)			0.38 (-1.5 to 2.2)			0.54 (-0.22 to 1.3)			0.18 (-0.70 to 1.1)
mean_StanceDur * H3000’s	14 (-23 to 52)			0.53 (-1.3 to 2.4)			0.05 (-0.73 to 0.83)			0.10 (-0.81 to 1.0)
subj_char.sd__(Intercept)	17 (NA to NA)			1.2 (NA to NA)			0.83 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	50 (NA to NA)			2.5 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_offset for Cluster: 7
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-20 (-50 to 9.3)	0.18	0.71	1.2 (-0.27 to 2.7)	0.11	0.43	-0.42 (-1.1 to 0.25)	0.22	0.57	1.7 (0.80 to 2.5)	<0.001	<0.001
mean_GaitCycleDur	4.5 (-11 to 20)	0.56	0.97	-0.47 (-1.2 to 0.28)	0.22	0.44	-0.09 (-0.40 to 0.22)	0.57	0.57	0.14 (-0.22 to 0.49)	0.45	0.85
group_char		0.97	0.97		0.66	0.83		0.31	0.57		0.85	0.85
H1000’s	—			—			—			—
H2000’s	1.2 (-52 to 55)			-0.87 (-3.6 to 1.9)			-0.76 (-2.0 to 0.44)			0.41 (-1.1 to 1.9)
H3000’s	-5.2 (-54 to 44)			-1.1 (-3.6 to 1.4)			0.23 (-0.88 to 1.4)			0.27 (-1.1 to 1.7)
mean_GaitCycleDur * group_char		0.78	0.97		0.83	0.83		0.44	0.57		0.83	0.85
mean_GaitCycleDur * H2000’s	7.1 (-24 to 38)			0.28 (-1.3 to 1.8)			0.42 (-0.22 to 1.1)			0.23 (-0.51 to 0.97)
mean_GaitCycleDur * H3000’s	10 (-21 to 41)			0.44 (-1.1 to 2.0)			0.06 (-0.60 to 0.72)			0.08 (-0.69 to 0.85)
subj_char.sd__(Intercept)	17 (NA to NA)			1.2 (NA to NA)			0.83 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	49 (NA to NA)			2.5 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in NA for Cluster: 7
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-13 (-37 to 10)	0.27	0.91	-0.49 (-1.7 to 0.74)	0.44	0.61	-0.55 (-1.1 to 0.01)	0.056	0.22	2.2 (1.4 to 2.9)	<0.001	<0.001
mean_PeakUpDownVel_mean	4.8 (-83 to 93)	0.91	0.91	3.7 (-0.65 to 8.1)	0.10	0.38	-0.13 (-1.9 to 1.7)	0.89	0.93	-1.2 (-3.3 to 0.90)	0.26	0.47
group_char		0.46	0.91		0.79	0.79		0.55	0.93		0.35	0.47
H1000’s	—			—			—			—
H2000’s	21 (-17 to 60)			0.36 (-1.6 to 2.3)			0.05 (-0.87 to 0.98)			0.89 (-0.33 to 2.1)
H3000’s	18 (-16 to 52)			0.62 (-1.1 to 2.4)			0.44 (-0.39 to 1.3)			0.21 (-0.88 to 1.3)
mean_PeakUpDownVel_mean * group_char		0.76	0.91		0.46	0.61		0.93	0.93		0.81	0.81
mean_PeakUpDownVel_mean * H2000’s	-39 (-175 to 97)			-2.9 (-9.7 to 3.8)			-0.52 (-3.3 to 2.3)			-0.51 (-3.8 to 2.8)
mean_PeakUpDownVel_mean * H3000’s	-43 (-164 to 78)			-3.7 (-9.8 to 2.3)			-0.31 (-2.8 to 2.2)			0.56 (-2.4 to 3.5)
subj_char.sd__(Intercept)	16 (NA to NA)			1.2 (NA to NA)			0.83 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	50 (NA to NA)			2.5 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_avg_power for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-7.6 (-47 to 32)	0.71	0.92	0.61 (-0.93 to 2.1)	0.44	0.68	-0.27 (-1.1 to 0.57)	0.53	0.62	0.86 (-0.18 to 1.9)	0.10	0.21
mean_APexc_COV	0.67 (-1.7 to 3.1)	0.59	0.92	-0.02 (-0.11 to 0.07)	0.65	0.68	-0.03 (-0.08 to 0.02)	0.28	0.62	0.02 (-0.04 to 0.07)	0.49	0.49
group_char		0.83	0.92		0.62	0.68		0.62	0.62		0.060	0.21
H1000’s	—			—			—			—
H2000’s	-18 (-80 to 43)			-1.2 (-3.6 to 1.2)			-0.67 (-2.0 to 0.67)			2.0 (0.34 to 3.7)
H3000’s	-3.7 (-62 to 54)			-0.56 (-2.8 to 1.7)			-0.24 (-1.5 to 1.1)			0.56 (-1.1 to 2.2)
mean_APexc_COV * group_char		0.92	0.92		0.68	0.68		0.31	0.62		0.19	0.25
mean_APexc_COV * H2000’s	0.05 (-3.1 to 3.2)			0.05 (-0.07 to 0.18)			0.05 (-0.01 to 0.12)			-0.06 (-0.13 to 0.02)
mean_APexc_COV * H3000’s	-0.44 (-3.4 to 2.5)			0.04 (-0.07 to 0.16)			0.03 (-0.03 to 0.09)			0.00 (-0.07 to 0.07)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.72 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	53 (NA to NA)			2.1 (NA to NA)			0.94 (NA to NA)			1.0 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in alpha_avg_power for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	7.6 (-27 to 42)	0.67	0.88	0.31 (-1.0 to 1.6)	0.65	0.86	-0.65 (-1.4 to 0.05)	0.068	0.27	0.97 (0.09 to 1.9)	0.031	0.13
mean_APexc_mean	-82 (-686 to 522)	0.79	0.88	-0.82 (-24 to 22)	0.94	0.94	-1.0 (-12 to 10)	0.86	0.86	3.7 (-8.7 to 16)	0.56	0.74
group_char		0.65	0.88		0.16	0.32		0.61	0.86		0.43	0.74
H1000’s	—			—			—			—
H2000’s	-23 (-73 to 27)			1.8 (-0.13 to 3.7)			0.50 (-0.55 to 1.5)			0.81 (-0.54 to 2.2)
H3000’s	-8.1 (-54 to 38)			0.43 (-1.3 to 2.2)			0.05 (-0.96 to 1.1)			0.67 (-0.63 to 2.0)
mean_APexc_mean * group_char		0.88	0.88		0.054	0.21		0.65	0.86		0.97	0.97
mean_APexc_mean * H2000’s	204 (-764 to 1,172)			-43 (-80 to -6.1)			-4.6 (-23 to 14)			2.1 (-19 to 23)
mean_APexc_mean * H3000’s	-49 (-983 to 884)			-3.4 (-39 to 32)			5.6 (-14 to 25)			2.3 (-19 to 24)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.75 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	53 (NA to NA)			2.0 (NA to NA)			0.93 (NA to NA)			1.0 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_avg_power for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-2.8 (-31 to 25)	0.84	0.84	0.31 (-0.77 to 1.4)	0.57	0.76	-0.62 (-1.3 to 0.07)	0.080	0.32	1.4 (0.45 to 2.3)	0.003	0.014
mean_MLexc_COV	0.41 (-1.4 to 2.2)	0.66	0.84	0.00 (-0.07 to 0.07)	0.93	0.93	-0.01 (-0.05 to 0.04)	0.78	0.78	-0.01 (-0.06 to 0.04)	0.59	0.59
group_char		0.17	0.55		0.29	0.76		0.65	0.78		0.052	0.10
H1000’s	—			—			—			—
H2000’s	-21 (-64 to 23)			-1.2 (-2.9 to 0.53)			-0.04 (-1.1 to 0.99)			1.6 (0.22 to 2.9)
H3000’s	-43 (-88 to 2.1)			0.20 (-1.6 to 2.0)			0.43 (-0.63 to 1.5)			0.21 (-1.2 to 1.6)
mean_MLexc_COV * group_char		0.28	0.55		0.42	0.76		0.59	0.78		0.076	0.10
mean_MLexc_COV * H2000’s	0.52 (-2.3 to 3.4)			0.07 (-0.04 to 0.18)			0.02 (-0.04 to 0.09)			-0.05 (-0.12 to 0.02)
mean_MLexc_COV * H3000’s	2.4 (-0.57 to 5.3)			0.01 (-0.11 to 0.12)			-0.01 (-0.07 to 0.06)			0.03 (-0.04 to 0.11)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.74 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	53 (NA to NA)			2.1 (NA to NA)			0.94 (NA to NA)			0.99 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_div_theta for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	18 (-11 to 48)	0.22	0.56	0.31 (-0.82 to 1.4)	0.59	0.79	-0.72 (-1.4 to -0.07)	0.030	0.12	0.77 (-0.06 to 1.6)	0.069	0.28
mean_MLexc_mean	-188 (-529 to 152)	0.28	0.56	-0.51 (-14 to 13)	0.94	0.94	0.08 (-6.9 to 7.0)	0.98	0.98	4.9 (-2.8 to 13)	0.21	0.28
group_char		0.46	0.61		0.10	0.19		0.80	0.98		0.15	0.28
H1000’s	—			—			—			—
H2000’s	-27 (-69 to 16)			1.4 (-0.20 to 3.0)			0.28 (-0.64 to 1.2)			0.80 (-0.42 to 2.0)
H3000’s	-9.1 (-50 to 31)			-0.22 (-1.8 to 1.3)			0.03 (-0.89 to 0.95)			1.2 (-0.04 to 2.4)
mean_MLexc_mean * group_char		0.72	0.72		0.017	0.069		0.75	0.98		0.43	0.43
mean_MLexc_mean * H2000’s	163 (-301 to 628)			-18 (-36 to 0.07)			0.17 (-9.0 to 9.3)			0.30 (-9.8 to 10)
mean_MLexc_mean * H3000’s	6.4 (-455 to 468)			6.3 (-11 to 24)			3.2 (-6.4 to 13)			-5.8 (-17 to 5.0)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.74 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	53 (NA to NA)			2.0 (NA to NA)			0.94 (NA to NA)			1.0 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_div_beta for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	12 (-27 to 51)	0.55	0.92	0.28 (-0.82 to 1.4)	0.62	0.83	-0.61 (-1.2 to 0.01)	0.053	0.21	0.93 (0.15 to 1.7)	0.019	0.076
mean_StepDur	-9.7 (-50 to 31)	0.64	0.92	-0.01 (-1.1 to 1.1)	0.98	0.98	-0.11 (-0.68 to 0.47)	0.72	0.84	0.27 (-0.31 to 0.85)	0.36	0.53
group_char		0.73	0.92		0.061	0.12		0.62	0.84		0.53	0.53
H1000’s	—			—			—			—
H2000’s	-28 (-97 to 41)			2.2 (0.30 to 4.2)			0.45 (-0.64 to 1.5)			0.76 (-0.56 to 2.1)
H3000’s	-6.7 (-77 to 64)			0.08 (-1.9 to 2.0)			0.45 (-0.70 to 1.6)			0.17 (-1.2 to 1.5)
mean_StepDur * group_char		0.92	0.92		0.020	0.080		0.84	0.84		0.44	0.53
mean_StepDur * H2000’s	17 (-66 to 100)			-3.2 (-5.5 to -0.84)			-0.22 (-1.4 to 0.98)			0.20 (-1.0 to 1.4)
mean_StepDur * H3000’s	7.6 (-84 to 99)			0.31 (-2.3 to 2.9)			-0.39 (-1.8 to 1.0)			0.97 (-0.51 to 2.4)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.78 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	73 (NA to NA)			2.0 (NA to NA)			1.0 (NA to NA)			1.0 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_beta_div_theta for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	8.0 (-16 to 32)	0.51	0.66	0.31 (-0.61 to 1.2)	0.51	0.91	-0.70 (-1.2 to -0.19)	0.008	0.030	0.96 (0.25 to 1.7)	0.008	0.033
mean_UDexc_COV	-0.39 (-2.1 to 1.3)	0.66	0.66	0.00 (-0.07 to 0.06)	0.91	0.91	0.00 (-0.03 to 0.03)	0.98	0.98	0.02 (-0.02 to 0.05)	0.35	0.46
group_char		0.44	0.66		0.84	0.91		0.69	0.98		0.11	0.22
H1000’s	—			—			—			—
H2000’s	-21 (-59 to 17)			0.39 (-1.1 to 1.9)			0.36 (-0.46 to 1.2)			1.1 (-0.02 to 2.2)
H3000’s	4.8 (-35 to 44)			0.38 (-1.2 to 1.9)			0.19 (-0.66 to 1.0)			0.89 (-0.25 to 2.0)
mean_UDexc_COV * group_char		0.59	0.66		0.73	0.91		0.92	0.98		0.77	0.77
mean_UDexc_COV * H2000’s	0.57 (-2.1 to 3.2)			-0.04 (-0.14 to 0.06)			0.00 (-0.05 to 0.05)			-0.02 (-0.07 to 0.03)
mean_UDexc_COV * H3000’s	-0.96 (-3.7 to 1.8)			-0.01 (-0.11 to 0.10)			0.01 (-0.05 to 0.06)			-0.01 (-0.07 to 0.04)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.74 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	53 (NA to NA)			2.1 (NA to NA)			0.94 (NA to NA)			1.0 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_theta_div_beta for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-3.1 (-31 to 25)	0.83	0.83	0.28 (-0.81 to 1.4)	0.62	0.82	-0.63 (-1.2 to -0.04)	0.036	0.14	1.4 (0.64 to 2.2)	<0.001	0.001
mean_UDexc_mean	261 (-849 to 1,371)	0.64	0.83	-0.53 (-44 to 43)	0.98	0.98	-3.4 (-24 to 18)	0.75	0.97	-9.9 (-33 to 13)	0.39	0.52
group_char		0.42	0.83		0.10	0.40		0.97	0.97		0.12	0.25
H1000’s	—			—			—			—
H2000’s	-20 (-62 to 23)			-1.3 (-3.0 to 0.35)			-0.11 (-1.0 to 0.79)			1.2 (0.00 to 2.4)
H3000’s	-26 (-68 to 15)			0.51 (-1.1 to 2.1)			-0.03 (-0.93 to 0.87)			0.82 (-0.37 to 2.0)
mean_UDexc_mean * group_char		0.69	0.83		0.20	0.40		0.53	0.97		0.73	0.73
mean_UDexc_mean * H2000’s	265 (-1,397 to 1,927)			48 (-17 to 112)			17 (-14 to 48)			-13 (-47 to 21)
mean_UDexc_mean * H3000’s	685 (-894 to 2,263)			-8.4 (-70 to 53)			13 (-18 to 44)			-3.6 (-37 to 30)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.73 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	53 (NA to NA)			2.1 (NA to NA)			0.94 (NA to NA)			0.99 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_exp for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	11 (-21 to 44)	0.50	0.85	0.28 (-0.63 to 1.2)	0.54	0.73	-0.61 (-1.2 to -0.07)	0.027	0.11	0.94 (0.23 to 1.7)	0.009	0.037
mean_StanceDur	-6.6 (-31 to 17)	0.59	0.85	-0.01 (-0.69 to 0.66)	0.97	0.97	-0.08 (-0.42 to 0.26)	0.66	0.95	0.19 (-0.16 to 0.53)	0.29	0.45
group_char		0.63	0.85		0.056	0.11		0.73	0.95		0.34	0.45
H1000’s	—			—			—			—
H2000’s	-28 (-85 to 29)			1.9 (0.29 to 3.5)			0.31 (-0.62 to 1.2)			0.88 (-0.30 to 2.1)
H3000’s	-9.7 (-69 to 49)			0.11 (-1.5 to 1.8)			0.31 (-0.66 to 1.3)			0.40 (-0.81 to 1.6)
mean_StanceDur * group_char		0.86	0.86		0.012	0.048		0.95	0.95		0.58	0.58
mean_StanceDur * H2000’s	12 (-37 to 62)			-2.0 (-3.4 to -0.62)			-0.03 (-0.73 to 0.68)			0.02 (-0.69 to 0.74)
mean_StanceDur * H3000’s	8.9 (-47 to 64)			0.20 (-1.4 to 1.7)			-0.14 (-0.97 to 0.69)			0.45 (-0.40 to 1.3)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.78 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	73 (NA to NA)			2.0 (NA to NA)			1.0 (NA to NA)			1.0 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_offset for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	12 (-27 to 51)	0.55	0.92	0.28 (-0.82 to 1.4)	0.62	0.83	-0.61 (-1.2 to 0.01)	0.053	0.21	0.93 (0.15 to 1.7)	0.019	0.076
mean_GaitCycleDur	-4.9 (-25 to 15)	0.64	0.92	-0.01 (-0.57 to 0.56)	0.98	0.98	-0.05 (-0.34 to 0.24)	0.72	0.83	0.14 (-0.16 to 0.43)	0.36	0.52
group_char		0.73	0.92		0.063	0.13		0.62	0.83		0.52	0.52
H1000’s	—			—			—			—
H2000’s	-28 (-97 to 41)			2.2 (0.29 to 4.2)			0.45 (-0.64 to 1.5)			0.76 (-0.55 to 2.1)
H3000’s	-7.0 (-77 to 63)			0.07 (-1.9 to 2.0)			0.46 (-0.69 to 1.6)			0.16 (-1.2 to 1.5)
mean_GaitCycleDur * group_char		0.92	0.92		0.021	0.083		0.83	0.83		0.44	0.52
mean_GaitCycleDur * H2000’s	8.5 (-33 to 50)			-1.6 (-2.7 to -0.41)			-0.11 (-0.70 to 0.49)			0.09 (-0.51 to 0.70)
mean_GaitCycleDur * H3000’s	4.0 (-42 to 50)			0.16 (-1.1 to 1.4)			-0.20 (-0.91 to 0.51)			0.48 (-0.25 to 1.2)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.78 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	73 (NA to NA)			2.0 (NA to NA)			1.0 (NA to NA)			1.0 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in NA for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-1.6 (-24 to 21)	0.89	0.89	0.26 (-0.62 to 1.1)	0.56	0.74	-0.67 (-1.2 to -0.19)	0.007	0.027	1.4 (0.68 to 2.0)	<0.001	<0.001
mean_PeakUpDownVel_mean	20 (-68 to 108)	0.66	0.89	0.01 (-3.4 to 3.4)	0.99	0.99	-0.16 (-1.8 to 1.4)	0.85	0.98	-0.78 (-2.5 to 0.92)	0.37	0.49
group_char		0.40	0.89		0.035	0.14		0.98	0.98		0.10	0.19
H1000’s	—			—			—			—
H2000’s	-19 (-54 to 16)			-1.3 (-2.7 to 0.04)			0.06 (-0.69 to 0.82)			1.1 (0.05 to 2.2)
H3000’s	-22 (-57 to 13)			0.55 (-0.81 to 1.9)			0.05 (-0.71 to 0.82)			0.81 (-0.26 to 1.9)
mean_PeakUpDownVel_mean * group_char		0.78	0.89		0.077	0.15		0.67	0.98		0.77	0.77
mean_PeakUpDownVel_mean * H2000’s	19 (-110 to 148)			4.5 (-0.43 to 9.5)			0.94 (-1.4 to 3.3)			-0.91 (-3.4 to 1.6)
mean_PeakUpDownVel_mean * H3000’s	45 (-80 to 171)			-0.90 (-5.8 to 4.0)			0.90 (-1.4 to 3.2)			-0.24 (-2.8 to 2.3)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.73 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	53 (NA to NA)			2.1 (NA to NA)			0.94 (NA to NA)			0.99 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_avg_power for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-2.8 (-26 to 21)	0.82	0.93	5.8 (-12 to 23)	0.52	0.99	0.15 (-1.2 to 1.5)	0.83	0.83	1.5 (0.02 to 2.9)	0.048	0.084
mean_APexc_COV	-0.14 (-1.6 to 1.3)	0.85	0.93	-0.21 (-1.3 to 0.87)	0.70	0.99	-0.01 (-0.09 to 0.07)	0.74	0.83	-0.03 (-0.11 to 0.06)	0.50	0.50
group_char		0.93	0.93		0.99	0.99		0.71	0.83		0.032	0.084
H1000’s	—			—			—			—
H2000’s	-1.2 (-35 to 32)			-0.09 (-25 to 25)			-0.71 (-2.6 to 1.2)			1.8 (-0.22 to 3.9)
H3000’s	4.0 (-26 to 34)			0.05 (-23 to 23)			-0.62 (-2.3 to 1.1)			-0.69 (-2.6 to 1.2)
mean_APexc_COV * group_char		0.86	0.93		0.98	0.99		0.77	0.83		0.063	0.084
mean_APexc_COV * H2000’s	0.42 (-1.4 to 2.2)			-0.01 (-1.3 to 1.3)			0.03 (-0.07 to 0.13)			-0.05 (-0.16 to 0.05)
mean_APexc_COV * H3000’s	0.11 (-1.5 to 1.8)			0.08 (-1.1 to 1.3)			0.03 (-0.06 to 0.12)			0.04 (-0.06 to 0.14)
subj_char.sd__(Intercept)	2.9 (NA to NA)			4.6 (NA to NA)			0.51 (NA to NA)			0.86 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			1.0 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in alpha_avg_power for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-0.01 (-19 to 19)	0.99	0.99	0.56 (-13 to 14)	0.94	0.94	-0.28 (-1.3 to 0.75)	0.59	0.71	1.1 (-0.01 to 2.3)	0.052	0.21
mean_APexc_mean	-88 (-408 to 232)	0.59	0.99	33 (-196 to 263)	0.78	0.94	3.9 (-13 to 21)	0.65	0.71	-2.4 (-20 to 15)	0.79	0.86
group_char		0.89	0.99		0.18	0.39		0.71	0.71		0.63	0.86
H1000’s	—			—			—			—
H2000’s	6.7 (-21 to 35)			-16 (-36 to 4.7)			0.63 (-0.94 to 2.2)			0.82 (-0.93 to 2.6)
H3000’s	1.3 (-24 to 26)			1.3 (-17 to 20)			0.44 (-0.95 to 1.8)			0.15 (-1.4 to 1.7)
mean_APexc_mean * group_char		0.95	0.99		0.20	0.39		0.61	0.71		0.86	0.86
mean_APexc_mean * H2000’s	-14 (-566 to 538)			336 (-66 to 738)			-14 (-45 to 16)			-8.6 (-41 to 23)
mean_APexc_mean * H3000’s	69 (-415 to 553)			-16 (-367 to 335)			-8.7 (-35 to 18)			-4.7 (-32 to 23)
subj_char.sd__(Intercept)	2.2 (NA to NA)			4.1 (NA to NA)			0.49 (NA to NA)			0.88 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_avg_power for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-9.7 (-28 to 8.9)	0.30	0.78	1.5 (-13 to 16)	0.84	0.89	-0.13 (-1.3 to 1.0)	0.83	0.90	0.90 (-0.46 to 2.3)	0.19	0.77
mean_MLexc_COV	0.32 (-0.86 to 1.5)	0.60	0.78	0.06 (-0.85 to 0.97)	0.89	0.89	0.00 (-0.07 to 0.08)	0.90	0.90	0.01 (-0.08 to 0.09)	0.88	0.88
group_char		0.66	0.78		0.71	0.89		0.61	0.90		0.49	0.88
H1000’s	—			—			—			—
H2000’s	4.4 (-22 to 31)			8.4 (-12 to 29)			-0.78 (-2.3 to 0.78)			1.1 (-0.76 to 2.9)
H3000’s	11 (-13 to 36)			2.8 (-16 to 22)			-0.27 (-1.7 to 1.2)			0.34 (-1.4 to 2.1)
mean_MLexc_COV * group_char		0.78	0.78		0.56	0.89		0.61	0.90		0.77	0.88
mean_MLexc_COV * H2000’s	0.19 (-1.5 to 1.9)			-0.68 (-2.0 to 0.60)			0.05 (-0.05 to 0.15)			-0.04 (-0.15 to 0.07)
mean_MLexc_COV * H3000’s	-0.38 (-2.0 to 1.2)			-0.19 (-1.4 to 1.0)			0.02 (-0.07 to 0.11)			-0.03 (-0.13 to 0.08)
subj_char.sd__(Intercept)	2.5 (NA to NA)			4.6 (NA to NA)			0.50 (NA to NA)			0.89 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_div_theta for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-4.6 (-23 to 14)	0.62	0.96	-1.3 (-15 to 12)	0.86	0.99	-0.04 (-1.1 to 0.99)	0.94	0.96	1.2 (0.06 to 2.4)	0.039	0.16
mean_MLexc_mean	-5.2 (-220 to 209)	0.96	0.96	46 (-112 to 205)	0.57	0.99	-0.29 (-12 to 12)	0.96	0.96	-2.9 (-16 to 9.8)	0.65	0.79
group_char		0.57	0.96		0.99	0.99		0.87	0.96		0.54	0.79
H1000’s	—			—			—			—
H2000’s	13 (-11 to 37)			-1.6 (-20 to 16)			0.14 (-1.2 to 1.5)			0.38 (-1.2 to 1.9)
H3000’s	6.2 (-17 to 29)			-0.86 (-18 to 16)			0.34 (-0.97 to 1.7)			-0.41 (-1.9 to 1.1)
mean_MLexc_mean * group_char		0.84	0.96		0.99	0.99		0.89	0.96		0.79	0.79
mean_MLexc_mean * H2000’s	-67 (-343 to 209)			-3.5 (-207 to 200)			-2.2 (-17 to 13)			1.3 (-15 to 17)
mean_MLexc_mean * H3000’s	-6.1 (-263 to 251)			4.4 (-186 to 195)			-3.5 (-18 to 11)			4.7 (-11 to 20)
subj_char.sd__(Intercept)	2.8 (NA to NA)			4.2 (NA to NA)			0.48 (NA to NA)			0.87 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_div_beta for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-11 (-28 to 4.9)	0.17	0.54	3.0 (-8.6 to 15)	0.61	0.81	-0.43 (-1.3 to 0.43)	0.33	0.35	1.4 (0.44 to 2.4)	0.004	0.017
mean_StepDur	6.7 (-9.5 to 23)	0.42	0.54	-0.61 (-12 to 11)	0.92	0.92	0.40 (-0.43 to 1.2)	0.35	0.35	-0.45 (-1.3 to 0.40)	0.30	0.60
group_char		0.27	0.54		0.11	0.22		0.13	0.27		0.99	0.99
H1000’s	—			—			—			—
H2000’s	22 (-5.1 to 49)			-21 (-40 to -1.4)			1.4 (-0.02 to 2.9)			0.09 (-1.5 to 1.7)
H3000’s	12 (-16 to 40)			-6.4 (-27 to 14)			0.88 (-0.61 to 2.4)			-0.04 (-1.7 to 1.6)
mean_StepDur * group_char		0.54	0.54		0.090	0.22		0.067	0.27		0.88	0.99
mean_StepDur * H2000’s	-18 (-49 to 14)			25 (2.6 to 48)			-1.9 (-3.5 to -0.22)			0.40 (-1.3 to 2.1)
mean_StepDur * H3000’s	-7.0 (-43 to 29)			9.1 (-16 to 35)			-1.1 (-3.0 to 0.75)			-0.12 (-2.1 to 1.8)
subj_char.sd__(Intercept)	2.6 (NA to NA)			3.9 (NA to NA)			0.51 (NA to NA)			0.88 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.0 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_beta_div_theta for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-6.9 (-21 to 6.7)	0.32	0.94	0.93 (-9.1 to 11)	0.86	0.86	-0.06 (-0.82 to 0.69)	0.87	0.99	1.1 (0.23 to 2.0)	0.013	0.054
mean_UDexc_COV	0.16 (-0.84 to 1.2)	0.76	0.94	0.12 (-0.59 to 0.84)	0.73	0.86	0.00 (-0.05 to 0.05)	0.99	0.99	-0.01 (-0.06 to 0.05)	0.76	0.76
group_char		0.60	0.94		0.49	0.86		0.51	0.99		0.40	0.76
H1000’s	—			—			—			—
H2000’s	10 (-12 to 33)			-9.7 (-26 to 6.6)			0.64 (-0.59 to 1.9)			0.78 (-0.61 to 2.2)
H3000’s	8.4 (-12 to 29)			-2.0 (-17 to 13)			-0.05 (-1.2 to 1.1)			-0.17 (-1.5 to 1.1)
mean_UDexc_COV * group_char		0.94	0.94		0.60	0.86		0.38	0.99		0.75	0.76
mean_UDexc_COV * H2000’s	-0.24 (-1.8 to 1.3)			0.57 (-0.55 to 1.7)			-0.05 (-0.13 to 0.03)			-0.02 (-0.11 to 0.06)
mean_UDexc_COV * H3000’s	-0.22 (-1.7 to 1.2)			0.14 (-0.91 to 1.2)			0.00 (-0.07 to 0.08)			0.01 (-0.07 to 0.09)
subj_char.sd__(Intercept)	2.1 (NA to NA)			4.4 (NA to NA)			0.48 (NA to NA)			0.88 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_theta_div_beta for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-2.5 (-19 to 14)	0.77	0.95	5.3 (-6.7 to 17)	0.39	0.92	-0.25 (-1.1 to 0.64)	0.58	0.64	0.98 (-0.03 to 2.0)	0.057	0.23
mean_UDexc_mean	-105 (-745 to 534)	0.75	0.95	-118 (-579 to 343)	0.62	0.92	8.0 (-26 to 42)	0.64	0.64	0.56 (-34 to 35)	0.98	0.98
group_char		0.95	0.95		0.92	0.92		0.34	0.64		0.69	0.98
H1000’s	—			—			—			—
H2000’s	1.9 (-22 to 26)			3.3 (-14 to 21)			-0.66 (-2.0 to 0.63)			0.59 (-0.88 to 2.0)
H3000’s	3.6 (-19 to 26)			0.43 (-16 to 17)			0.27 (-0.97 to 1.5)			0.05 (-1.4 to 1.5)
mean_UDexc_mean * group_char		0.89	0.95		0.77	0.92		0.30	0.64		0.98	0.98
mean_UDexc_mean * H2000’s	224 (-709 to 1,157)			-216 (-889 to 457)			26 (-23 to 75)			-4.8 (-56 to 46)
mean_UDexc_mean * H3000’s	83 (-763 to 928)			-8.0 (-625 to 609)			-10 (-56 to 35)			-2.5 (-51 to 46)
subj_char.sd__(Intercept)	2.2 (NA to NA)			4.2 (NA to NA)			0.45 (NA to NA)			0.88 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_exp for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-10 (-24 to 3.7)	0.15	0.56	2.9 (-7.1 to 13)	0.57	0.76	-0.38 (-1.1 to 0.37)	0.32	0.33	1.3 (0.48 to 2.2)	0.002	0.009
mean_StanceDur	4.0 (-5.8 to 14)	0.42	0.56	-0.34 (-7.3 to 6.6)	0.92	0.92	0.25 (-0.25 to 0.74)	0.33	0.33	-0.27 (-0.78 to 0.24)	0.30	0.60
group_char		0.28	0.56		0.13	0.27		0.17	0.33		0.92	0.94
H1000’s	—			—			—			—
H2000’s	18 (-4.8 to 40)			-17 (-33 to -0.28)			1.1 (-0.08 to 2.4)			0.26 (-1.1 to 1.6)
H3000’s	11 (-13 to 34)			-4.5 (-21 to 12)			0.66 (-0.58 to 1.9)			-0.03 (-1.4 to 1.4)
mean_StanceDur * group_char		0.63	0.63		0.11	0.27		0.074	0.30		0.94	0.94
mean_StanceDur * H2000’s	-9.2 (-28 to 9.7)			14 (0.89 to 28)			-1.1 (-2.1 to -0.12)			0.14 (-0.87 to 1.2)
mean_StanceDur * H3000’s	-3.9 (-25 to 17)			4.7 (-10 to 20)			-0.60 (-1.7 to 0.49)			-0.08 (-1.2 to 1.1)
subj_char.sd__(Intercept)	2.4 (NA to NA)			3.8 (NA to NA)			0.50 (NA to NA)			0.88 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.0 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_offset for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-11 (-27 to 4.9)	0.17	0.54	3.0 (-8.6 to 15)	0.61	0.81	-0.43 (-1.3 to 0.43)	0.33	0.34	1.4 (0.44 to 2.4)	0.004	0.017
mean_GaitCycleDur	3.4 (-4.7 to 11)	0.42	0.54	-0.30 (-6.0 to 5.4)	0.92	0.92	0.20 (-0.21 to 0.61)	0.34	0.34	-0.22 (-0.65 to 0.20)	0.30	0.60
group_char		0.27	0.54		0.11	0.22		0.13	0.27		0.99	0.99
H1000’s	—			—			—			—
H2000’s	22 (-5.0 to 49)			-21 (-40 to -1.4)			1.4 (-0.02 to 2.9)			0.09 (-1.5 to 1.7)
H3000’s	12 (-16 to 40)			-6.4 (-26 to 14)			0.88 (-0.61 to 2.4)			-0.04 (-1.7 to 1.6)
mean_GaitCycleDur * group_char		0.54	0.54		0.090	0.22		0.066	0.27		0.88	0.99
mean_GaitCycleDur * H2000’s	-8.8 (-25 to 7.0)			13 (1.3 to 24)			-0.93 (-1.7 to -0.11)			0.20 (-0.66 to 1.1)
mean_GaitCycleDur * H3000’s	-3.5 (-21 to 14)			4.5 (-8.2 to 17)			-0.55 (-1.5 to 0.37)			-0.06 (-1.0 to 0.91)
subj_char.sd__(Intercept)	2.6 (NA to NA)			3.9 (NA to NA)			0.51 (NA to NA)			0.88 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.0 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in NA for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-3.8 (-17 to 9.6)	0.58	0.91	3.5 (-6.3 to 13)	0.48	0.87	-0.05 (-0.78 to 0.69)	0.90	0.96	0.92 (0.08 to 1.8)	0.032	0.13
mean_PeakUpDownVel_mean	-5.2 (-55 to 45)	0.84	0.91	-4.4 (-40 to 32)	0.81	0.87	-0.06 (-2.7 to 2.5)	0.96	0.96	0.29 (-2.4 to 2.9)	0.83	0.94
group_char		0.91	0.91		0.87	0.87		0.45	0.89		0.65	0.94
H1000’s	—			—			—			—
H2000’s	1.6 (-18 to 21)			3.5 (-11 to 18)			-0.57 (-1.6 to 0.52)			0.58 (-0.67 to 1.8)
H3000’s	4.1 (-15 to 23)			2.9 (-11 to 17)			0.09 (-0.95 to 1.1)			0.16 (-1.0 to 1.4)
mean_PeakUpDownVel_mean * group_char		0.81	0.91		0.74	0.87		0.40	0.89		0.94	0.94
mean_PeakUpDownVel_mean * H2000’s	23 (-49 to 94)			-20 (-71 to 31)			2.0 (-1.7 to 5.7)			-0.45 (-4.3 to 3.4)
mean_PeakUpDownVel_mean * H3000’s	6.0 (-61 to 73)			-10 (-59 to 38)			-0.29 (-3.8 to 3.3)			-0.66 (-4.4 to 3.0)
subj_char.sd__(Intercept)	2.3 (NA to NA)			4.0 (NA to NA)			0.47 (NA to NA)			0.88 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_avg_power for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	9.0 (-14 to 32)	0.44	0.83	0.62 (-14 to 15)	0.93	0.97	-0.55 (-1.7 to 0.65)	0.37	0.49	0.89 (-0.17 to 2.0)	0.10	0.14
mean_APexc_COV	-0.33 (-1.6 to 0.97)	0.62	0.83	0.01 (-0.80 to 0.83)	0.97	0.97	0.02 (-0.04 to 0.09)	0.52	0.52	-0.01 (-0.07 to 0.04)	0.65	0.65
group_char		0.86	0.86		0.79	0.97		0.28	0.49		0.10	0.14
H1000’s	—			—			—			—
H2000’s	5.7 (-34 to 45)			6.0 (-20 to 32)			0.69 (-1.4 to 2.8)			-1.7 (-3.7 to 0.20)
H3000’s	-5.0 (-36 to 26)			-3.1 (-24 to 17)			1.4 (-0.31 to 3.1)			0.34 (-1.2 to 1.9)
mean_APexc_COV * group_char		0.39	0.83		0.97	0.97		0.37	0.49		0.007	0.030
mean_APexc_COV * H2000’s	-0.67 (-2.6 to 1.3)			-0.10 (-1.3 to 1.1)			-0.03 (-0.13 to 0.07)			0.13 (0.05 to 0.22)
mean_APexc_COV * H3000’s	0.45 (-1.1 to 2.0)			0.03 (-0.93 to 1.0)			-0.06 (-0.14 to 0.02)			0.03 (-0.04 to 0.09)
subj_char.sd__(Intercept)	7.9 (NA to NA)			8.7 (NA to NA)			0.76 (NA to NA)			1.0 (NA to NA)
Residual.sd__Observation	23 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.87 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in alpha_avg_power for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	3.9 (-14 to 22)	0.68	0.90	1.2 (-11 to 13)	0.85	0.95	-0.36 (-1.3 to 0.62)	0.47	0.63	0.46 (-0.43 to 1.4)	0.31	0.42
mean_APexc_mean	-7.9 (-335 to 320)	0.96	0.96	-6.3 (-212 to 199)	0.95	0.95	3.2 (-13 to 20)	0.70	0.70	4.1 (-9.8 to 18)	0.56	0.56
group_char		0.003	0.006		0.86	0.95		0.015	0.030		0.020	0.039
H1000’s	—			—			—			—
H2000’s	51 (20 to 81)			-4.5 (-25 to 16)			2.4 (0.73 to 4.0)			-0.37 (-1.9 to 1.1)
H3000’s	7.8 (-16 to 32)			0.87 (-16 to 17)			0.43 (-0.89 to 1.8)			1.4 (0.20 to 2.7)
mean_APexc_mean * group_char		<0.001	<0.001		0.47	0.95		0.009	0.030		0.006	0.026
mean_APexc_mean * H2000’s	-1,476 (-2,124 to -829)			198 (-220 to 616)			-52 (-86 to -18)			37 (8.0 to 65)
mean_APexc_mean * H3000’s	-98 (-572 to 376)			-71 (-383 to 240)			-6.6 (-32 to 18)			-12 (-33 to 9.8)
subj_char.sd__(Intercept)	4.5 (NA to NA)			8.6 (NA to NA)			0.71 (NA to NA)			0.94 (NA to NA)
Residual.sd__Observation	22 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.89 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_avg_power for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-7.3 (-26 to 11)	0.45	0.45	0.14 (-13 to 13)	0.98	0.98	0.49 (-0.60 to 1.6)	0.38	0.75	0.96 (-0.09 to 2.0)	0.073	0.15
mean_MLexc_COV	0.74 (-0.48 to 2.0)	0.23	0.45	0.05 (-0.79 to 0.88)	0.91	0.98	-0.05 (-0.12 to 0.02)	0.18	0.73	-0.02 (-0.08 to 0.04)	0.54	0.54
group_char		0.45	0.45		0.26	0.98		0.96	0.98		0.31	0.41
H1000’s	—			—			—			—
H2000’s	19 (-11 to 49)			5.1 (-15 to 25)			0.24 (-1.4 to 1.9)			-0.26 (-1.8 to 1.3)
H3000’s	11 (-16 to 37)			-10 (-28 to 7.7)			0.11 (-1.4 to 1.6)			0.81 (-0.60 to 2.2)
mean_MLexc_COV * group_char		0.12	0.45		0.49	0.98		0.98	0.98		0.060	0.15
mean_MLexc_COV * H2000’s	-2.2 (-4.3 to -0.09)			-0.09 (-1.4 to 1.2)			-0.01 (-0.12 to 0.10)			0.10 (0.01 to 0.20)
mean_MLexc_COV * H3000’s	-0.48 (-2.2 to 1.3)			0.58 (-0.57 to 1.7)			0.00 (-0.09 to 0.09)			0.01 (-0.08 to 0.09)
subj_char.sd__(Intercept)	7.4 (NA to NA)			8.9 (NA to NA)			0.75 (NA to NA)			0.98 (NA to NA)
Residual.sd__Observation	23 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.90 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_div_theta for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	11 (-5.9 to 29)	0.20	0.67	1.5 (-9.6 to 13)	0.79	0.89	-0.72 (-1.7 to 0.23)	0.14	0.28	0.24 (-0.65 to 1.1)	0.59	0.74
mean_MLexc_mean	-98 (-297 to 101)	0.33	0.67	-8.6 (-131 to 113)	0.89	0.89	6.6 (-3.8 to 17)	0.21	0.28	5.3 (-3.7 to 14)	0.25	0.49
group_char		0.68	0.91		0.18	0.36		0.27	0.28		0.075	0.30
H1000’s	—			—			—			—
H2000’s	-4.8 (-30 to 21)			1.4 (-15 to 18)			1.1 (-0.25 to 2.5)			1.3 (-0.04 to 2.6)
H3000’s	5.6 (-17 to 28)			12 (-2.3 to 27)			0.48 (-0.78 to 1.7)			1.3 (0.06 to 2.5)
mean_MLexc_mean * group_char		0.91	0.91		0.017	0.067		0.28	0.28		0.74	0.74
mean_MLexc_mean * H2000’s	-58 (-336 to 220)			29 (-137 to 194)			-11 (-25 to 2.8)			-2.2 (-14 to 9.9)
mean_MLexc_mean * H3000’s	-14 (-263 to 235)			-166 (-320 to -12)			-4.6 (-18 to 8.5)			-4.5 (-16 to 7.0)
subj_char.sd__(Intercept)	7.4 (NA to NA)			8.8 (NA to NA)			0.75 (NA to NA)			0.98 (NA to NA)
Residual.sd__Observation	23 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.91 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_div_beta for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	3.4 (-13 to 20)	0.69	0.91	1.6 (-8.8 to 12)	0.76	0.87	-0.32 (-1.2 to 0.55)	0.48	0.63	0.29 (-0.52 to 1.1)	0.49	0.49
mean_StepDur	0.06 (-17 to 17)	0.99	0.99	-0.87 (-11 to 9.2)	0.87	0.87	0.14 (-0.69 to 0.98)	0.74	0.74	0.43 (-0.26 to 1.1)	0.22	0.43
group_char		0.13	0.25		0.34	0.67		0.087	0.17		0.077	0.31
H1000’s	—			—			—			—
H2000’s	28 (-3.0 to 58)			-1.7 (-21 to 17)			1.6 (0.00 to 3.2)			0.67 (-0.78 to 2.1)
H3000’s	21 (-5.7 to 48)			12 (-5.6 to 29)			-0.23 (-1.7 to 1.2)			1.5 (0.20 to 2.8)
mean_StepDur * group_char		0.018	0.071		0.10	0.39		0.078	0.17		0.32	0.43
mean_StepDur * H2000’s	-51 (-88 to -14)			7.2 (-15 to 29)			-1.9 (-3.7 to -0.02)			0.68 (-0.85 to 2.2)
mean_StepDur * H3000’s	-25 (-60 to 8.6)			-20 (-41 to 0.90)			0.56 (-1.2 to 2.3)			-0.76 (-2.2 to 0.72)
subj_char.sd__(Intercept)	6.6 (NA to NA)			8.4 (NA to NA)			0.72 (NA to NA)			0.97 (NA to NA)
Residual.sd__Observation	22 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.90 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_beta_div_theta for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	6.0 (-7.8 to 20)	0.40	0.53	1.1 (-8.0 to 10)	0.81	0.95	-0.38 (-1.1 to 0.37)	0.32	0.53	0.41 (-0.31 to 1.1)	0.27	0.30
mean_UDexc_COV	-0.20 (-1.2 to 0.78)	0.69	0.69	-0.02 (-0.61 to 0.57)	0.95	0.95	0.02 (-0.03 to 0.06)	0.53	0.53	0.02 (-0.02 to 0.06)	0.30	0.30
group_char		0.37	0.53		0.84	0.95		0.49	0.53		0.065	0.20
H1000’s	—			—			—			—
H2000’s	6.4 (-16 to 29)			2.4 (-13 to 17)			0.71 (-0.54 to 2.0)			0.50 (-0.68 to 1.7)
H3000’s	15 (-6.0 to 36)			4.2 (-9.8 to 18)			0.04 (-1.1 to 1.2)			1.3 (0.21 to 2.4)
mean_UDexc_COV * group_char		0.25	0.53		0.48	0.95		0.51	0.53		0.10	0.20
mean_UDexc_COV * H2000’s	-1.3 (-2.9 to 0.31)			0.11 (-0.85 to 1.1)			-0.04 (-0.12 to 0.04)			0.05 (-0.02 to 0.11)
mean_UDexc_COV * H3000’s	-0.83 (-2.3 to 0.64)			-0.46 (-1.4 to 0.45)			0.01 (-0.07 to 0.08)			-0.03 (-0.09 to 0.03)
subj_char.sd__(Intercept)	7.0 (NA to NA)			8.8 (NA to NA)			0.75 (NA to NA)			0.98 (NA to NA)
Residual.sd__Observation	22 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.89 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_theta_div_beta for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	1.4 (-16 to 18)	0.87	0.87	-0.08 (-11 to 11)	0.99	0.99	0.10 (-0.80 to 1.0)	0.83	0.83	1.1 (0.27 to 1.9)	0.010	0.039
mean_UDexc_mean	91 (-608 to 789)	0.80	0.87	41 (-385 to 468)	0.85	0.99	-13 (-48 to 22)	0.48	0.64	-19 (-48 to 10)	0.21	0.22
group_char		0.23	0.66		0.31	0.99		0.47	0.64		0.11	0.22
H1000’s	—			—			—			—
H2000’s	-21 (-46 to 3.9)			4.9 (-11 to 21)			-0.25 (-1.6 to 1.1)			1.3 (0.06 to 2.6)
H3000’s	-14 (-37 to 9.0)			-7.3 (-22 to 7.9)			0.54 (-0.71 to 1.8)			0.34 (-0.83 to 1.5)
mean_UDexc_mean * group_char		0.33	0.66		0.64	0.99		0.34	0.64		0.22	0.22
mean_UDexc_mean * H2000’s	424 (-546 to 1,394)			-47 (-640 to 547)			19 (-30 to 67)			-7.3 (-48 to 33)
mean_UDexc_mean * H3000’s	679 (-215 to 1,573)			195 (-358 to 747)			-14 (-60 to 31)			24 (-14 to 62)
subj_char.sd__(Intercept)	7.6 (NA to NA)			8.7 (NA to NA)			0.75 (NA to NA)			0.99 (NA to NA)
Residual.sd__Observation	22 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.90 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_exp for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	3.3 (-11 to 17)	0.65	0.86	1.5 (-7.6 to 11)	0.74	0.86	-0.28 (-1.0 to 0.47)	0.47	0.62	0.38 (-0.35 to 1.1)	0.31	0.37
mean_StanceDur	0.16 (-10 to 10)	0.97	0.97	-0.54 (-6.6 to 5.5)	0.86	0.86	0.08 (-0.42 to 0.58)	0.77	0.77	0.24 (-0.17 to 0.66)	0.25	0.37
group_char		0.20	0.40		0.48	0.86		0.14	0.28		0.064	0.26
H1000’s	—			—			—			—
H2000’s	18 (-7.8 to 43)			0.10 (-16 to 16)			1.2 (-0.14 to 2.5)			0.77 (-0.49 to 2.0)
H3000’s	18 (-4.5 to 41)			8.5 (-6.1 to 23)			-0.16 (-1.4 to 1.1)			1.3 (0.21 to 2.5)
mean_StanceDur * group_char		0.030	0.12		0.13	0.51		0.11	0.28		0.37	0.37
mean_StanceDur * H2000’s	-28 (-50 to -5.9)			3.6 (-9.6 to 17)			-1.0 (-2.1 to 0.09)			0.39 (-0.52 to 1.3)
mean_StanceDur * H3000’s	-16 (-36 to 5.2)			-12 (-24 to 1.1)			0.33 (-0.72 to 1.4)			-0.41 (-1.3 to 0.47)
subj_char.sd__(Intercept)	6.9 (NA to NA)			8.5 (NA to NA)			0.73 (NA to NA)			0.98 (NA to NA)
Residual.sd__Observation	22 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.90 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_offset for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	3.4 (-13 to 20)	0.68	0.91	1.6 (-8.8 to 12)	0.76	0.87	-0.32 (-1.2 to 0.55)	0.47	0.63	0.29 (-0.52 to 1.1)	0.49	0.49
mean_GaitCycleDur	0.02 (-8.4 to 8.5)	0.99	0.99	-0.43 (-5.5 to 4.6)	0.87	0.87	0.07 (-0.34 to 0.49)	0.73	0.73	0.21 (-0.13 to 0.56)	0.23	0.43
group_char		0.12	0.25		0.34	0.67		0.085	0.17		0.078	0.31
H1000’s	—			—			—			—
H2000’s	28 (-2.8 to 58)			-1.7 (-21 to 17)			1.6 (0.00 to 3.2)			0.66 (-0.78 to 2.1)
H3000’s	21 (-5.6 to 48)			12 (-5.6 to 29)			-0.23 (-1.7 to 1.2)			1.5 (0.20 to 2.8)
mean_GaitCycleDur * group_char		0.017	0.068		0.10	0.39		0.076	0.17		0.32	0.43
mean_GaitCycleDur * H2000’s	-26 (-44 to -7.2)			3.6 (-7.5 to 15)			-0.93 (-1.8 to -0.02)			0.34 (-0.42 to 1.1)
mean_GaitCycleDur * H3000’s	-13 (-30 to 4.3)			-10 (-21 to 0.45)			0.28 (-0.59 to 1.1)			-0.38 (-1.1 to 0.36)
subj_char.sd__(Intercept)	6.6 (NA to NA)			8.4 (NA to NA)			0.72 (NA to NA)			0.97 (NA to NA)
Residual.sd__Observation	22 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.90 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in NA for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	0.13 (-13 to 13)	0.98	0.98	0.26 (-8.4 to 8.9)	0.95	0.95	0.11 (-0.61 to 0.82)	0.77	0.77	0.93 (0.24 to 1.6)	0.009	0.035
mean_PeakUpDownVel_mean	15 (-35 to 64)	0.57	0.76	2.6 (-28 to 33)	0.87	0.95	-1.3 (-3.7 to 1.2)	0.31	0.42	-1.1 (-3.2 to 0.95)	0.29	0.29
group_char		0.15	0.58		0.094	0.38		0.26	0.42		0.050	0.10
H1000’s	—			—			—			—
H2000’s	-20 (-41 to 0.00)			6.8 (-6.7 to 20)			-0.43 (-1.5 to 0.68)			1.4 (0.27 to 2.5)
H3000’s	-9.6 (-28 to 8.7)			-7.9 (-20 to 4.2)			0.49 (-0.52 to 1.5)			0.50 (-0.49 to 1.5)
mean_PeakUpDownVel_mean * group_char		0.38	0.75		0.26	0.53		0.10	0.39		0.19	0.25
mean_PeakUpDownVel_mean * H2000’s	35 (-36 to 107)			-12 (-55 to 32)			2.5 (-1.0 to 6.0)			-0.88 (-3.8 to 2.1)
mean_PeakUpDownVel_mean * H3000’s	45 (-19 to 109)			20 (-19 to 60)			-1.1 (-4.3 to 2.1)			1.6 (-1.1 to 4.3)
subj_char.sd__(Intercept)	7.0 (NA to NA)			8.5 (NA to NA)			0.73 (NA to NA)			0.98 (NA to NA)
Residual.sd__Observation	22 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.90 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_avg_power for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	3.8 (-65 to 73)	0.91	0.97	4.0 (-7.3 to 15)	0.49	0.75	-0.41 (-1.4 to 0.59)	0.42	0.88	0.63 (-0.62 to 1.9)	0.32	0.89
mean_APexc_COV	-0.09 (-4.3 to 4.1)	0.97	0.97	-0.11 (-0.80 to 0.58)	0.75	0.75	0.01 (-0.05 to 0.07)	0.73	0.88	0.00 (-0.08 to 0.07)	0.90	0.90
group_char		0.27	0.94		0.67	0.75		0.72	0.88		0.45	0.89
H1000’s	—			—			—			—
H2000’s	-10 (-115 to 95)			3.3 (-14 to 20)			-0.59 (-2.1 to 0.96)			0.70 (-1.3 to 2.7)
H3000’s	-75 (-172 to 23)			-4.4 (-20 to 11)			-0.46 (-1.9 to 0.97)			1.2 (-0.66 to 3.0)
mean_APexc_COV * group_char		0.47	0.94		0.49	0.75		0.88	0.88		0.74	0.90
mean_APexc_COV * H2000’s	0.07 (-5.4 to 5.5)			-0.23 (-1.1 to 0.66)			0.02 (-0.06 to 0.10)			0.03 (-0.07 to 0.13)
mean_APexc_COV * H3000’s	2.3 (-2.6 to 7.2)			0.19 (-0.61 to 0.98)			0.00 (-0.07 to 0.07)			0.00 (-0.09 to 0.08)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.52 (NA to NA)			0.96 (NA to NA)
Residual.sd__Observation	79 (NA to NA)			13 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in alpha_avg_power for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	4.3 (-59 to 68)	0.89	0.95	2.7 (-7.5 to 13)	0.61	0.81	-0.24 (-1.1 to 0.63)	0.59	0.99	0.66 (-0.42 to 1.7)	0.23	0.83
mean_APexc_mean	-37 (-1,167 to 1,093)	0.95	0.95	-9.0 (-191 to 173)	0.92	0.92	-0.04 (-15 to 15)	0.99	0.99	-2.0 (-20 to 16)	0.83	0.83
group_char		0.70	0.95		0.046	0.16		0.93	0.99		0.50	0.83
H1000’s	—			—			—			—
H2000’s	-7.4 (-101 to 86)			-15 (-30 to -0.15)			-0.09 (-1.4 to 1.2)			0.95 (-0.69 to 2.6)
H3000’s	-32 (-111 to 47)			1.1 (-12 to 14)			-0.21 (-1.3 to 0.92)			0.63 (-0.82 to 2.1)
mean_APexc_mean * group_char		0.80	0.95		0.079	0.16		0.99	0.99		0.74	0.83
mean_APexc_mean * H2000’s	-58 (-1,951 to 1,836)			289 (-16 to 593)			-1.1 (-27 to 25)			7.5 (-24 to 39)
mean_APexc_mean * H3000’s	469 (-1,119 to 2,057)			-47 (-303 to 208)			-1.2 (-24 to 21)			11 (-17 to 38)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.52 (NA to NA)			0.96 (NA to NA)
Residual.sd__Observation	80 (NA to NA)			13 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_avg_power for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	1.7 (-56 to 60)	0.95	0.98	3.7 (-5.7 to 13)	0.44	0.84	-0.31 (-1.2 to 0.57)	0.49	0.87	0.05 (-1.1 to 1.2)	0.94	0.94
mean_MLexc_COV	0.04 (-3.9 to 4.0)	0.98	0.98	-0.11 (-0.75 to 0.53)	0.74	0.84	0.00 (-0.05 to 0.06)	0.87	0.87	0.04 (-0.04 to 0.11)	0.34	0.68
group_char		0.57	0.98		0.84	0.84		0.80	0.87		0.022	0.090
H1000’s	—			—			—			—
H2000’s	-14 (-91 to 64)			-0.89 (-14 to 12)			0.14 (-1.0 to 1.3)			2.0 (0.57 to 3.5)
H3000’s	-46 (-132 to 41)			-4.1 (-18 to 10)			0.42 (-0.85 to 1.7)			1.5 (-0.10 to 3.1)
mean_MLexc_COV * group_char		0.71	0.98		0.73	0.84		0.54	0.87		0.53	0.70
mean_MLexc_COV * H2000’s	0.30 (-5.0 to 5.6)			-0.12 (-0.98 to 0.74)			-0.02 (-0.10 to 0.06)			-0.05 (-0.15 to 0.04)
mean_MLexc_COV * H3000’s	2.2 (-3.5 to 8.0)			0.24 (-0.69 to 1.2)			-0.05 (-0.13 to 0.04)			-0.03 (-0.13 to 0.07)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.54 (NA to NA)			0.96 (NA to NA)
Residual.sd__Observation	80 (NA to NA)			13 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_div_theta for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	3.0 (-52 to 57)	0.92	0.98	3.1 (-5.7 to 12)	0.49	0.66	-0.27 (-1.0 to 0.50)	0.49	0.94	0.89 (-0.09 to 1.9)	0.074	0.29
mean_MLexc_mean	-8.2 (-645 to 628)	0.98	0.98	-11 (-114 to 92)	0.83	0.83	0.34 (-8.3 to 9.0)	0.94	0.94	-4.2 (-15 to 6.3)	0.43	0.58
group_char		0.81	0.98		0.22	0.66		0.48	0.94		0.35	0.58
H1000’s	—			—			—			—
H2000’s	-8.5 (-80 to 63)			-8.8 (-20 to 2.6)			-0.42 (-1.4 to 0.60)			0.96 (-0.34 to 2.3)
H3000’s	-22 (-93 to 48)			-1.0 (-12 to 10)			-0.63 (-1.7 to 0.40)			0.62 (-0.71 to 2.0)
mean_MLexc_mean * group_char		0.92	0.98		0.40	0.66		0.73	0.94		0.73	0.73
mean_MLexc_mean * H2000’s	-10 (-794 to 774)			71 (-56 to 197)			3.0 (-7.6 to 14)			4.1 (-8.9 to 17)
mean_MLexc_mean * H3000’s	120 (-693 to 933)			5.4 (-126 to 137)			4.6 (-6.7 to 16)			5.5 (-8.4 to 19)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.55 (NA to NA)			0.96 (NA to NA)
Residual.sd__Observation	80 (NA to NA)			13 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_div_beta for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	1.0 (-50 to 52)	0.97	0.97	1.8 (-6.5 to 10)	0.67	0.89	-0.04 (-0.73 to 0.66)	0.92	0.92	0.69 (-0.18 to 1.6)	0.12	0.47
mean_StepDur	1.4 (-52 to 55)	0.96	0.97	0.42 (-8.2 to 9.1)	0.92	0.92	-0.23 (-0.91 to 0.46)	0.51	0.69	-0.16 (-0.96 to 0.65)	0.70	0.70
group_char		0.59	0.97		0.18	0.56		0.18	0.56		0.52	0.70
H1000’s	—			—			—			—
H2000’s	0.28 (-84 to 85)			-11 (-25 to 2.3)			-0.53 (-1.7 to 0.62)			0.83 (-0.60 to 2.3)
H3000’s	-45 (-135 to 46)			2.2 (-13 to 17)			-1.2 (-2.5 to 0.08)			0.35 (-1.3 to 2.0)
mean_StepDur * group_char		0.67	0.97		0.28	0.56		0.28	0.56		0.53	0.70
mean_StepDur * H2000’s	-13 (-114 to 88)			12 (-4.5 to 28)			0.47 (-0.84 to 1.8)			0.58 (-0.98 to 2.1)
mean_StepDur * H3000’s	50 (-74 to 174)			-4.1 (-24 to 16)			1.4 (-0.36 to 3.1)			1.1 (-1.1 to 3.2)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.53 (NA to NA)			0.95 (NA to NA)
Residual.sd__Observation	80 (NA to NA)			13 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_beta_div_theta for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-0.11 (-44 to 43)	0.99	0.99	3.4 (-3.7 to 10)	0.35	0.86	-0.15 (-0.76 to 0.45)	0.62	0.74	0.61 (-0.18 to 1.4)	0.13	0.27
mean_UDexc_COV	0.19 (-3.0 to 3.4)	0.91	0.99	-0.10 (-0.62 to 0.43)	0.72	0.86	-0.01 (-0.05 to 0.03)	0.74	0.74	0.00 (-0.06 to 0.05)	0.85	0.85
group_char		0.33	0.94		0.62	0.86		0.031	0.12		0.13	0.27
H1000’s	—			—			—			—
H2000’s	-11 (-76 to 54)			-5.2 (-16 to 5.4)			-0.74 (-1.6 to 0.16)			1.2 (0.01 to 2.4)
H3000’s	-51 (-120 to 17)			-1.3 (-13 to 9.9)			-1.2 (-2.2 to -0.30)			0.73 (-0.51 to 2.0)
mean_UDexc_COV * group_char		0.47	0.94		0.86	0.86		0.076	0.15		0.81	0.85
mean_UDexc_COV * H2000’s	0.11 (-4.5 to 4.7)			0.21 (-0.55 to 0.97)			0.05 (-0.01 to 0.11)			0.01 (-0.06 to 0.08)
mean_UDexc_COV * H3000’s	2.7 (-2.1 to 7.4)			0.06 (-0.71 to 0.84)			0.07 (0.01 to 0.13)			0.02 (-0.05 to 0.10)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.51 (NA to NA)			0.96 (NA to NA)
Residual.sd__Observation	79 (NA to NA)			13 (NA to NA)			0.99 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_theta_div_beta for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	2.3 (-46 to 50)	0.93	0.99	2.3 (-5.7 to 10)	0.57	0.80	-0.25 (-0.91 to 0.42)	0.47	0.62	0.43 (-0.43 to 1.3)	0.33	0.65
mean_UDexc_mean	0.79 (-1,903 to 1,905)	0.99	0.99	-3.6 (-318 to 311)	0.98	0.98	0.20 (-25 to 25)	0.99	0.99	5.1 (-25 to 35)	0.74	0.74
group_char		0.16	0.32		0.39	0.80		0.32	0.62		0.015	0.062
H1000’s	—			—			—			—
H2000’s	-6.4 (-72 to 60)			-6.3 (-17 to 4.6)			0.33 (-0.59 to 1.3)			1.7 (0.49 to 2.9)
H3000’s	53 (-15 to 122)			0.57 (-11 to 12)			0.74 (-0.22 to 1.7)			1.3 (0.08 to 2.6)
mean_UDexc_mean * group_char		0.076	0.30		0.60	0.80		0.090	0.36		0.72	0.74
mean_UDexc_mean * H2000’s	-129 (-2,710 to 2,453)			157 (-269 to 583)			-20 (-54 to 15)			-17 (-58 to 24)
mean_UDexc_mean * H3000’s	-2,584 (-5,172 to 2.9)			-45 (-472 to 383)			-39 (-74 to -4.1)			-11 (-53 to 32)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.48 (NA to NA)			0.96 (NA to NA)
Residual.sd__Observation	78 (NA to NA)			13 (NA to NA)			0.99 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_exp for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	1.2 (-42 to 44)	0.96	0.96	1.9 (-5.0 to 8.8)	0.59	0.79	-0.05 (-0.64 to 0.53)	0.86	0.86	0.68 (-0.08 to 1.4)	0.077	0.31
mean_StanceDur	0.92 (-31 to 33)	0.95	0.96	0.25 (-4.9 to 5.4)	0.92	0.92	-0.15 (-0.56 to 0.25)	0.46	0.62	-0.11 (-0.58 to 0.37)	0.66	0.66
group_char		0.61	0.96		0.15	0.51		0.081	0.27		0.30	0.59
H1000’s	—			—			—			—
H2000’s	-2.8 (-73 to 67)			-9.6 (-21 to 1.7)			-0.46 (-1.4 to 0.49)			0.96 (-0.26 to 2.2)
H3000’s	-37 (-114 to 39)			2.4 (-10 to 15)			-1.2 (-2.3 to -0.15)			0.49 (-0.87 to 1.8)
mean_StanceDur * group_char		0.71	0.96		0.25	0.51		0.14	0.27		0.56	0.66
mean_StanceDur * H2000’s	-6.4 (-67 to 54)			7.1 (-2.7 to 17)			0.29 (-0.49 to 1.1)			0.30 (-0.62 to 1.2)
mean_StanceDur * H3000’s	28 (-47 to 104)			-3.3 (-16 to 9.0)			1.0 (0.00 to 2.0)			0.62 (-0.61 to 1.9)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.54 (NA to NA)			0.95 (NA to NA)
Residual.sd__Observation	80 (NA to NA)			13 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_offset for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	1.0 (-50 to 52)	0.97	0.97	1.8 (-6.5 to 10)	0.67	0.89	-0.04 (-0.73 to 0.66)	0.92	0.92	0.69 (-0.18 to 1.6)	0.12	0.47
mean_GaitCycleDur	0.69 (-26 to 27)	0.96	0.97	0.21 (-4.1 to 4.5)	0.92	0.92	-0.11 (-0.45 to 0.23)	0.51	0.68	-0.08 (-0.48 to 0.32)	0.70	0.70
group_char		0.59	0.97		0.18	0.56		0.18	0.55		0.52	0.70
H1000’s	—			—			—			—
H2000’s	0.30 (-84 to 85)			-11 (-25 to 2.3)			-0.53 (-1.7 to 0.62)			0.83 (-0.60 to 2.3)
H3000’s	-45 (-135 to 46)			2.2 (-12 to 17)			-1.2 (-2.5 to 0.08)			0.34 (-1.3 to 2.0)
mean_GaitCycleDur * group_char		0.66	0.97		0.28	0.56		0.28	0.55		0.53	0.70
mean_GaitCycleDur * H2000’s	-6.3 (-57 to 44)			5.9 (-2.3 to 14)			0.24 (-0.42 to 0.89)			0.29 (-0.49 to 1.1)
mean_GaitCycleDur * H3000’s	25 (-37 to 87)			-2.0 (-12 to 8.0)			0.68 (-0.18 to 1.5)			0.53 (-0.53 to 1.6)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.53 (NA to NA)			0.95 (NA to NA)
Residual.sd__Observation	80 (NA to NA)			13 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in NA for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	3.2 (-36 to 42)	0.87	0.96	2.1 (-4.4 to 8.6)	0.53	0.97	-0.33 (-0.88 to 0.21)	0.23	0.42	0.50 (-0.22 to 1.2)	0.17	0.35
mean_PeakUpDownVel_mean	-4.0 (-154 to 146)	0.96	0.96	0.43 (-24 to 25)	0.97	0.97	0.38 (-1.6 to 2.3)	0.70	0.70	0.21 (-2.1 to 2.5)	0.86	0.86
group_char		0.10	0.19		0.62	0.97		0.32	0.42		0.007	0.028
H1000’s	—			—			—			—
H2000’s	-8.3 (-64 to 47)			-4.1 (-13 to 5.1)			0.26 (-0.53 to 1.0)			1.6 (0.60 to 2.7)
H3000’s	51 (-6.3 to 108)			-0.19 (-9.7 to 9.3)			0.63 (-0.18 to 1.4)			1.1 (0.02 to 2.2)
mean_PeakUpDownVel_mean * group_char		0.036	0.14		0.88	0.97		0.061	0.24		0.63	0.84
mean_PeakUpDownVel_mean * H2000’s	-4.5 (-209 to 200)			6.3 (-28 to 40)			-1.6 (-4.2 to 1.1)			-1.4 (-4.6 to 1.8)
mean_PeakUpDownVel_mean * H3000’s	-224 (-426 to -23)			-1.5 (-35 to 32)			-3.2 (-5.8 to -0.55)			-0.13 (-3.3 to 3.1)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.50 (NA to NA)			0.95 (NA to NA)
Residual.sd__Observation	78 (NA to NA)			13 (NA to NA)			0.99 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_avg_power for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	23 (-15 to 61)	0.23	0.46	-2.0 (-15 to 12)	0.77	0.89	-0.45 (-1.5 to 0.63)	0.42	0.89	0.53 (-0.68 to 1.7)	0.39	0.39
mean_APexc_COV	-1.4 (-3.7 to 0.88)	0.23	0.46	0.06 (-0.77 to 0.90)	0.89	0.89	0.00 (-0.06 to 0.07)	0.89	0.89	0.04 (-0.02 to 0.11)	0.22	0.29
group_char		0.61	0.61		0.47	0.89		0.76	0.89		0.047	0.19
H1000’s	—			—			—			—
H2000’s	-30 (-88 to 29)			12 (-8.5 to 33)			-0.59 (-2.3 to 1.1)			1.9 (-0.13 to 3.9)
H3000’s	-14 (-65 to 38)			1.8 (-16 to 20)			-0.44 (-1.9 to 1.1)			2.0 (0.28 to 3.7)
mean_APexc_COV * group_char		0.58	0.61		0.64	0.89		0.88	0.89		0.19	0.29
mean_APexc_COV * H2000’s	1.5 (-1.5 to 4.5)			-0.41 (-1.5 to 0.66)			0.02 (-0.07 to 0.11)			-0.06 (-0.15 to 0.03)
mean_APexc_COV * H3000’s	1.2 (-1.5 to 3.9)			-0.04 (-1.0 to 0.92)			0.01 (-0.07 to 0.08)			-0.07 (-0.15 to 0.01)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.52 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	39 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.95 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in alpha_avg_power for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	6.2 (-25 to 38)	0.70	0.89	-7.5 (-19 to 4.0)	0.20	0.33	-0.53 (-1.4 to 0.35)	0.24	0.82	1.1 (0.11 to 2.1)	0.030	0.12
mean_APexc_mean	-104 (-645 to 437)	0.71	0.89	120 (-84 to 323)	0.25	0.33	2.9 (-12 to 18)	0.70	0.82	1.2 (-13 to 15)	0.87	0.87
group_char		0.75	0.89		0.25	0.33		0.82	0.82		0.35	0.70
H1000’s	—			—			—			—
H2000’s	-6.2 (-51 to 38)			14 (-2.5 to 30)			-0.41 (-1.7 to 0.86)			0.94 (-0.53 to 2.4)
H3000’s	9.0 (-31 to 49)			8.0 (-6.5 to 23)			-0.22 (-1.4 to 0.93)			0.88 (-0.49 to 2.3)
mean_APexc_mean * group_char		0.89	0.89		0.41	0.41		0.80	0.82		0.81	0.87
mean_APexc_mean * H2000’s	7.9 (-820 to 836)			-204 (-511 to 103)			7.6 (-16 to 31)			-1.5 (-23 to 20)
mean_APexc_mean * H3000’s	-166 (-947 to 614)			-123 (-408 to 161)			1.5 (-21 to 24)			-7.0 (-29 to 15)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.54 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	39 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.95 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_avg_power for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	17 (-13 to 46)	0.26	0.35	3.1 (-7.2 to 13)	0.56	0.86	0.06 (-0.81 to 0.93)	0.90	0.90	0.60 (-0.49 to 1.7)	0.28	0.28
mean_MLexc_COV	-1.1 (-3.0 to 0.77)	0.25	0.35	-0.27 (-0.93 to 0.38)	0.41	0.86	-0.03 (-0.08 to 0.03)	0.30	0.40	0.04 (-0.02 to 0.10)	0.20	0.27
group_char		0.26	0.35		0.86	0.86		0.12	0.34		0.063	0.25
H1000’s	—			—			—			—
H2000’s	-29 (-69 to 11)			0.89 (-13 to 15)			-0.40 (-1.6 to 0.78)			1.5 (-0.01 to 3.0)
H3000’s	-1.7 (-43 to 40)			-3.0 (-18 to 12)			-1.2 (-2.5 to -0.03)			1.6 (0.16 to 3.1)
mean_MLexc_COV * group_char		0.40	0.40		0.84	0.86		0.17	0.34		0.20	0.27
mean_MLexc_COV * H2000’s	1.7 (-0.91 to 4.2)			0.15 (-0.77 to 1.1)			0.02 (-0.05 to 0.10)			-0.04 (-0.12 to 0.04)
mean_MLexc_COV * H3000’s	0.35 (-2.3 to 3.0)			0.29 (-0.66 to 1.2)			0.07 (-0.01 to 0.15)			-0.07 (-0.15 to 0.01)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.53 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	39 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.94 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_div_theta for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	4.0 (-24 to 32)	0.78	0.97	-5.6 (-15 to 4.2)	0.26	0.44	-0.65 (-1.4 to 0.15)	0.11	0.44	1.2 (0.21 to 2.1)	0.018	0.070
mean_MLexc_mean	-43 (-367 to 280)	0.79	0.97	58 (-59 to 175)	0.33	0.44	3.4 (-5.7 to 13)	0.46	0.55	-0.09 (-9.2 to 9.0)	0.98	0.98
group_char		0.97	0.97		0.32	0.44		0.55	0.55		0.27	0.54
H1000’s	—			—			—			—
H2000’s	-3.9 (-42 to 34)			10 (-3.2 to 24)			-0.37 (-1.5 to 0.71)			1.1 (-0.24 to 2.5)
H3000’s	0.16 (-35 to 36)			6.0 (-6.5 to 19)			0.17 (-0.85 to 1.2)			0.64 (-0.66 to 1.9)
mean_MLexc_mean * group_char		0.96	0.97		0.53	0.53		0.34	0.55		0.87	0.98
mean_MLexc_mean * H2000’s	-4.4 (-408 to 399)			-84 (-232 to 63)			2.4 (-8.9 to 14)			-2.6 (-14 to 8.4)
mean_MLexc_mean * H3000’s	44 (-360 to 447)			-59 (-205 to 86)			-4.6 (-16 to 6.8)			-0.74 (-12 to 11)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.52 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	40 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.95 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_div_beta for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	1.2 (-24 to 27)	0.93	0.96	-2.9 (-12 to 6.5)	0.55	0.75	-0.49 (-1.2 to 0.22)	0.18	0.71	1.1 (0.26 to 2.0)	0.011	0.045
mean_StepDur	-0.70 (-26 to 25)	0.96	0.96	2.1 (-7.6 to 12)	0.67	0.75	0.13 (-0.56 to 0.82)	0.72	0.76	0.05 (-0.57 to 0.67)	0.87	0.87
group_char		0.52	0.96		0.54	0.75		0.72	0.76		0.26	0.52
H1000’s	—			—			—			—
H2000’s	-5.0 (-49 to 39)			9.3 (-7.1 to 26)			-0.42 (-1.6 to 0.81)			1.2 (-0.25 to 2.6)
H3000’s	20 (-21 to 61)			3.7 (-11 to 19)			-0.40 (-1.6 to 0.77)			0.62 (-0.75 to 2.0)
mean_StepDur * group_char		0.63	0.96		0.75	0.75		0.76	0.76		0.83	0.87
mean_StepDur * H2000’s	-0.22 (-51 to 50)			-7.4 (-27 to 12)			0.47 (-0.92 to 1.9)			-0.38 (-1.6 to 0.88)
mean_StepDur * H3000’s	-24 (-76 to 27)			-2.7 (-22 to 16)			0.35 (-1.1 to 1.8)			-0.04 (-1.4 to 1.3)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.54 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	39 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.95 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_beta_div_theta for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-3.0 (-26 to 20)	0.79	0.85	-1.5 (-9.9 to 7.0)	0.73	0.99	-0.54 (-1.2 to 0.11)	0.11	0.42	1.1 (0.30 to 2.0)	0.007	0.029
mean_UDexc_COV	0.29 (-1.4 to 1.9)	0.73	0.85	0.04 (-0.59 to 0.66)	0.91	0.99	0.01 (-0.03 to 0.06)	0.57	0.99	0.00 (-0.04 to 0.04)	0.87	0.87
group_char		0.63	0.85		0.86	0.99		0.88	0.99		0.18	0.37
H1000’s	—			—			—			—
H2000’s	-4.7 (-38 to 28)			3.5 (-8.7 to 16)			-0.12 (-1.1 to 0.82)			1.1 (-0.13 to 2.3)
H3000’s	12 (-22 to 45)			1.9 (-11 to 14)			-0.25 (-1.2 to 0.71)			0.80 (-0.39 to 2.0)
mean_UDexc_COV * group_char		0.85	0.85		0.99	0.99		0.99	0.99		0.80	0.87
mean_UDexc_COV * H2000’s	-0.05 (-2.3 to 2.2)			-0.02 (-0.88 to 0.85)			0.00 (-0.06 to 0.07)			-0.02 (-0.08 to 0.04)
mean_UDexc_COV * H3000’s	-0.61 (-2.9 to 1.7)			-0.05 (-0.92 to 0.83)			0.00 (-0.06 to 0.07)			-0.02 (-0.08 to 0.04)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.52 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	40 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.96 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_theta_div_beta for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	3.8 (-22 to 30)	0.77	0.92	-0.68 (-10 to 8.9)	0.89	0.98	-0.20 (-0.94 to 0.54)	0.59	0.62	1.4 (0.49 to 2.3)	0.002	0.010
mean_UDexc_mean	-138 (-1,159 to 883)	0.79	0.92	-14 (-397 to 369)	0.94	0.98	-7.2 (-35 to 21)	0.62	0.62	-9.2 (-35 to 17)	0.49	0.80
group_char		0.72	0.92		0.98	0.98		0.43	0.62		0.80	0.80
H1000’s	—			—			—			—
H2000’s	-8.3 (-46 to 30)			-0.41 (-14 to 14)			0.18 (-0.90 to 1.3)			0.44 (-0.88 to 1.8)
H3000’s	7.1 (-29 to 43)			0.81 (-12 to 14)			-0.48 (-1.5 to 0.54)			0.29 (-0.96 to 1.5)
mean_UDexc_mean * group_char		0.92	0.92		0.84	0.98		0.54	0.62		0.63	0.80
mean_UDexc_mean * H2000’s	135 (-1,290 to 1,560)			145 (-388 to 679)			-9.5 (-49 to 30)			17 (-19 to 54)
mean_UDexc_mean * H3000’s	-140 (-1,518 to 1,237)			21 (-493 to 535)			12 (-26 to 50)			12 (-24 to 48)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.53 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	40 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.95 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_exp for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	0.53 (-21 to 22)	0.96	0.99	-2.5 (-10 to 5.5)	0.54	0.69	-0.44 (-1.1 to 0.17)	0.16	0.62	1.1 (0.32 to 1.9)	0.006	0.025
mean_StanceDur	0.04 (-15 to 15)	0.99	0.99	1.2 (-4.6 to 7.0)	0.69	0.69	0.06 (-0.36 to 0.47)	0.79	0.79	0.04 (-0.33 to 0.41)	0.83	0.85
group_char		0.48	0.99		0.45	0.69		0.72	0.79		0.22	0.45
H1000’s	—			—			—			—
H2000’s	-5.5 (-42 to 31)			8.7 (-4.7 to 22)			-0.33 (-1.4 to 0.69)			1.1 (-0.17 to 2.4)
H3000’s	17 (-17 to 52)			3.1 (-9.6 to 16)			-0.36 (-1.3 to 0.63)			0.63 (-0.59 to 1.9)
mean_StanceDur * group_char		0.62	0.99		0.69	0.69		0.79	0.79		0.85	0.85
mean_StanceDur * H2000’s	0.40 (-29 to 30)			-5.0 (-16 to 6.4)			0.26 (-0.56 to 1.1)			-0.22 (-0.96 to 0.52)
mean_StanceDur * H3000’s	-15 (-46 to 16)			-1.6 (-13 to 10)			0.20 (-0.66 to 1.1)			-0.05 (-0.84 to 0.75)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.54 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	39 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.95 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_offset for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	1.2 (-24 to 27)	0.92	0.96	-2.9 (-12 to 6.5)	0.55	0.75	-0.49 (-1.2 to 0.22)	0.18	0.71	1.1 (0.26 to 2.0)	0.011	0.044
mean_GaitCycleDur	-0.35 (-13 to 12)	0.96	0.96	1.0 (-3.8 to 5.9)	0.67	0.75	0.06 (-0.28 to 0.41)	0.72	0.76	0.03 (-0.28 to 0.34)	0.87	0.87
group_char		0.52	0.96		0.54	0.75		0.72	0.76		0.26	0.52
H1000’s	—			—			—			—
H2000’s	-5.0 (-49 to 39)			9.2 (-7.1 to 26)			-0.42 (-1.6 to 0.81)			1.2 (-0.24 to 2.6)
H3000’s	20 (-21 to 61)			3.7 (-11 to 19)			-0.40 (-1.6 to 0.76)			0.61 (-0.75 to 2.0)
mean_GaitCycleDur * group_char		0.63	0.96		0.75	0.75		0.76	0.76		0.83	0.87
mean_GaitCycleDur * H2000’s	-0.13 (-25 to 25)			-3.7 (-13 to 5.9)			0.23 (-0.46 to 0.92)			-0.19 (-0.82 to 0.44)
mean_GaitCycleDur * H3000’s	-12 (-38 to 13)			-1.4 (-11 to 8.2)			0.18 (-0.54 to 0.89)			-0.02 (-0.69 to 0.66)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.54 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	39 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.95 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in NA for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	1.8 (-19 to 23)	0.87	0.98	-1.2 (-8.9 to 6.6)	0.77	0.97	-0.14 (-0.74 to 0.46)	0.64	0.64	1.3 (0.48 to 2.1)	0.002	0.007
mean_PeakUpDownVel_mean	-5.0 (-83 to 73)	0.90	0.98	0.73 (-29 to 31)	0.96	0.97	-0.97 (-3.1 to 1.2)	0.37	0.64	-0.44 (-2.4 to 1.5)	0.65	0.81
group_char		0.78	0.98		0.97	0.97		0.39	0.64		0.52	0.81
H1000’s	—			—			—			—
H2000’s	-7.0 (-38 to 24)			1.2 (-10 to 13)			0.05 (-0.84 to 0.94)			0.64 (-0.54 to 1.8)
H3000’s	4.0 (-26 to 34)			1.2 (-9.6 to 12)			-0.49 (-1.3 to 0.35)			0.50 (-0.62 to 1.6)
mean_PeakUpDownVel_mean * group_char		0.98	0.98		0.92	0.97		0.51	0.64		0.81	0.81
mean_PeakUpDownVel_mean * H2000’s	7.9 (-102 to 118)			7.6 (-34 to 49)			-0.37 (-3.4 to 2.6)			0.88 (-1.8 to 3.6)
mean_PeakUpDownVel_mean * H3000’s	-0.98 (-105 to 103)			0.39 (-39 to 40)			1.2 (-1.7 to 4.1)			0.34 (-2.3 to 3.0)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.53 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	40 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.96 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_avg_power for Cluster: 13
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	14 (-18 to 45)	0.39	0.53	1.0 (-4.6 to 6.7)	0.73	0.86	-0.58 (-1.6 to 0.49)	0.29	0.49	1.0 (-0.20 to 2.3)	0.10	0.26
mean_APexc_COV	-0.76 (-2.7 to 1.2)	0.45	0.53	-0.03 (-0.38 to 0.32)	0.86	0.86	0.02 (-0.05 to 0.08)	0.56	0.56	-0.01 (-0.08 to 0.07)	0.86	0.90
group_char		0.36	0.53		0.47	0.86		0.30	0.49		0.13	0.26
H1000’s	—			—			—			—
H2000’s	-26 (-76 to 23)			-3.2 (-12 to 5.7)			-0.07 (-1.7 to 1.6)			2.0 (0.05 to 4.0)
H3000’s	-29 (-71 to 13)			2.2 (-5.4 to 9.9)			1.0 (-0.46 to 2.5)			0.72 (-1.0 to 2.4)
mean_APexc_COV * group_char		0.53	0.53		0.85	0.86		0.36	0.49		0.90	0.90
mean_APexc_COV * H2000’s	0.95 (-1.7 to 3.6)			0.09 (-0.37 to 0.56)			-0.01 (-0.09 to 0.08)			-0.02 (-0.12 to 0.07)
mean_APexc_COV * H3000’s	1.3 (-0.94 to 3.5)			-0.01 (-0.40 to 0.39)			-0.04 (-0.11 to 0.03)			-0.02 (-0.10 to 0.07)
subj_char.sd__(Intercept)	0.00 (NA to NA)			2.4 (NA to NA)			0.79 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	31 (NA to NA)			4.9 (NA to NA)			0.81 (NA to NA)			0.89 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in alpha_avg_power for Cluster: 13
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-2.3 (-29 to 24)	0.86	0.86	0.65 (-3.7 to 5.0)	0.77	0.95	0.01 (-0.79 to 0.82)	0.98	0.98	0.83 (-0.12 to 1.8)	0.086	0.34
mean_APexc_mean	80 (-382 to 542)	0.74	0.86	-2.2 (-77 to 72)	0.95	0.95	-5.4 (-18 to 7.5)	0.41	0.84	1.9 (-12 to 16)	0.79	0.79
group_char		0.48	0.86		0.045	0.18		0.65	0.87		0.20	0.40
H1000’s	—			—			—			—
H2000’s	20 (-18 to 59)			-0.99 (-7.6 to 5.6)			-0.31 (-1.6 to 0.93)			1.4 (-0.12 to 2.8)
H3000’s	1.0 (-32 to 34)			5.7 (0.04 to 11)			-0.51 (-1.6 to 0.57)			0.50 (-0.80 to 1.8)
mean_APexc_mean * group_char		0.18	0.74		0.16	0.32		0.42	0.84		0.71	0.79
mean_APexc_mean * H2000’s	-653 (-1,392 to 85)			-8.1 (-132 to 115)			4.4 (-18 to 26)			3.4 (-21 to 28)
mean_APexc_mean * H3000’s	-82 (-710 to 547)			-97 (-202 to 9.4)			13 (-6.3 to 32)			-6.8 (-28 to 15)
subj_char.sd__(Intercept)	1.7 (NA to NA)			2.5 (NA to NA)			0.76 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	31 (NA to NA)			4.8 (NA to NA)			0.82 (NA to NA)			0.90 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_avg_power for Cluster: 13
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	1.6 (-18 to 21)	0.87	0.96	0.51 (-3.3 to 4.3)	0.79	0.99	-0.31 (-1.1 to 0.47)	0.44	0.94	1.1 (0.10 to 2.0)	0.031	0.062
mean_MLexc_COV	0.03 (-1.2 to 1.3)	0.96	0.96	0.00 (-0.24 to 0.24)	0.99	0.99	0.00 (-0.05 to 0.05)	0.94	0.94	-0.01 (-0.06 to 0.05)	0.77	0.77
group_char		0.042	0.17		0.45	0.91		0.94	0.94		0.009	0.036
H1000’s	—			—			—			—
H2000’s	-41 (-74 to -8.3)			-1.3 (-7.2 to 4.6)			0.20 (-0.98 to 1.4)			2.0 (0.53 to 3.4)
H3000’s	-6.6 (-39 to 26)			-3.8 (-9.6 to 2.1)			0.00 (-1.2 to 1.2)			-0.04 (-1.4 to 1.4)
mean_MLexc_COV * group_char		0.12	0.23		0.10	0.41		0.79	0.94		0.48	0.64
mean_MLexc_COV * H2000’s	2.3 (0.06 to 4.5)			0.00 (-0.39 to 0.39)			-0.02 (-0.09 to 0.05)			-0.04 (-0.12 to 0.05)
mean_MLexc_COV * H3000’s	0.22 (-1.9 to 2.3)			0.37 (0.00 to 0.75)			0.01 (-0.06 to 0.08)			0.02 (-0.06 to 0.10)
subj_char.sd__(Intercept)	4.8 (NA to NA)			2.5 (NA to NA)			0.77 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	31 (NA to NA)			4.8 (NA to NA)			0.82 (NA to NA)			0.89 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_div_theta for Cluster: 13
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-2.1 (-23 to 19)	0.85	0.85	0.65 (-3.1 to 4.4)	0.74	0.94	-0.11 (-0.84 to 0.62)	0.76	0.86	0.81 (-0.05 to 1.7)	0.066	0.26
mean_MLexc_mean	54 (-205 to 314)	0.68	0.85	-1.7 (-47 to 44)	0.94	0.94	-2.3 (-10 to 5.8)	0.58	0.86	1.6 (-7.4 to 11)	0.73	0.73
group_char		0.091	0.18		0.18	0.72		0.84	0.86		0.21	0.41
H1000’s	—			—			—			—
H2000’s	27 (-3.3 to 57)			-1.6 (-7.1 to 3.9)			-0.30 (-1.4 to 0.78)			1.2 (-0.12 to 2.5)
H3000’s	-3.2 (-31 to 25)			3.2 (-1.9 to 8.4)			-0.04 (-1.1 to 0.97)			0.45 (-0.77 to 1.7)
mean_MLexc_mean * group_char		0.011	0.045		0.70	0.94		0.86	0.86		0.47	0.63
mean_MLexc_mean * H2000’s	-418 (-759 to -77)			3.4 (-56 to 63)			2.9 (-7.7 to 14)			3.3 (-8.6 to 15)
mean_MLexc_mean * H3000’s	-10 (-331 to 311)			-17 (-74 to 40)			1.8 (-8.4 to 12)			-3.2 (-15 to 8.2)
subj_char.sd__(Intercept)	3.7 (NA to NA)			2.5 (NA to NA)			0.77 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	30 (NA to NA)			4.9 (NA to NA)			0.82 (NA to NA)			0.90 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_div_beta for Cluster: 13
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-3.8 (-23 to 16)	0.70	0.70	0.67 (-2.7 to 4.0)	0.70	0.92	-0.19 (-0.83 to 0.45)	0.56	0.92	0.87 (0.10 to 1.6)	0.027	0.11
mean_StepDur	6.3 (-14 to 26)	0.53	0.70	-0.16 (-3.4 to 3.1)	0.92	0.92	-0.10 (-0.66 to 0.45)	0.71	0.92	0.08 (-0.53 to 0.68)	0.80	0.80
group_char		0.003	0.006		0.036	0.14		0.92	0.92		0.68	0.80
H1000’s	—			—			—			—
H2000’s	63 (26 to 100)			-0.50 (-6.9 to 5.9)			-0.23 (-1.4 to 0.97)			0.63 (-0.77 to 2.0)
H3000’s	4.8 (-28 to 38)			7.1 (1.3 to 13)			-0.16 (-1.3 to 0.94)			0.15 (-1.2 to 1.4)
mean_StepDur * group_char		<0.001	<0.001		0.092	0.18		0.86	0.92		0.28	0.55
mean_StepDur * H2000’s	-95 (-140 to -50)			-1.1 (-8.5 to 6.3)			0.19 (-1.1 to 1.5)			1.1 (-0.26 to 2.6)
mean_StepDur * H3000’s	-9.8 (-52 to 32)			-8.0 (-15 to -0.81)			0.34 (-0.94 to 1.6)			0.09 (-1.3 to 1.5)
subj_char.sd__(Intercept)	0.00 (NA to NA)			2.6 (NA to NA)			0.77 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	30 (NA to NA)			4.8 (NA to NA)			0.82 (NA to NA)			0.89 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_beta_div_theta for Cluster: 13
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	3.5 (-14 to 21)	0.69	0.86	0.61 (-2.4 to 3.6)	0.69	0.93	-0.32 (-0.92 to 0.27)	0.28	0.50	0.92 (0.19 to 1.6)	0.013	0.026
mean_UDexc_COV	-0.12 (-1.4 to 1.2)	0.86	0.86	-0.01 (-0.22 to 0.21)	0.95	0.95	0.00 (-0.03 to 0.04)	0.87	0.87	0.00 (-0.04 to 0.04)	0.94	0.94
group_char		0.74	0.86		0.14	0.55		0.37	0.50		0.006	0.024
H1000’s	—			—			—			—
H2000’s	2.0 (-25 to 29)			-1.4 (-6.1 to 3.3)			-0.37 (-1.3 to 0.56)			1.7 (0.54 to 2.8)
H3000’s	-9.8 (-39 to 20)			4.0 (-1.1 to 9.1)			0.39 (-0.59 to 1.4)			-0.09 (-1.3 to 1.1)
mean_UDexc_COV * group_char		0.42	0.86		0.57	0.93		0.36	0.50		0.62	0.83
mean_UDexc_COV * H2000’s	-0.93 (-2.9 to 1.0)			0.01 (-0.31 to 0.33)			0.02 (-0.03 to 0.08)			-0.01 (-0.08 to 0.05)
mean_UDexc_COV * H3000’s	0.47 (-1.6 to 2.6)			-0.16 (-0.51 to 0.18)			-0.02 (-0.08 to 0.04)			0.02 (-0.05 to 0.09)
subj_char.sd__(Intercept)	3.6 (NA to NA)			2.4 (NA to NA)			0.78 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	31 (NA to NA)			4.9 (NA to NA)			0.81 (NA to NA)			0.90 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_theta_div_beta for Cluster: 13
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	13 (-7.5 to 33)	0.22	0.27	0.44 (-3.0 to 3.9)	0.80	0.96	-0.35 (-1.0 to 0.30)	0.30	0.59	0.90 (0.11 to 1.7)	0.025	0.055
mean_UDexc_mean	-444 (-1,233 to 344)	0.27	0.27	3.4 (-126 to 133)	0.96	0.96	2.6 (-19 to 25)	0.82	0.82	1.4 (-23 to 26)	0.91	0.91
group_char		0.075	0.27		0.84	0.96		0.46	0.62		0.028	0.055
H1000’s	—			—			—			—
H2000’s	-36 (-66 to -4.9)			-1.3 (-6.6 to 4.0)			0.45 (-0.55 to 1.5)			1.7 (0.45 to 2.9)
H3000’s	-14 (-44 to 16)			0.30 (-4.9 to 5.5)			-0.21 (-1.2 to 0.78)			0.61 (-0.59 to 1.8)
mean_UDexc_mean * group_char		0.22	0.27		0.81	0.96		0.17	0.59		0.66	0.88
mean_UDexc_mean * H2000’s	1,038 (-137 to 2,214)			-2.7 (-196 to 191)			-21 (-54 to 12)			-7.4 (-44 to 29)
mean_UDexc_mean * H3000’s	425 (-734 to 1,584)			56 (-138 to 249)			12 (-21 to 45)			-17 (-54 to 20)
subj_char.sd__(Intercept)	4.5 (NA to NA)			2.5 (NA to NA)			0.76 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	31 (NA to NA)			4.9 (NA to NA)			0.81 (NA to NA)			0.90 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_exp for Cluster: 13
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-2.6 (-19 to 14)	0.76	0.76	0.65 (-2.2 to 3.6)	0.66	0.88	-0.20 (-0.77 to 0.37)	0.49	0.96	0.87 (0.17 to 1.6)	0.015	0.059
mean_StanceDur	3.7 (-8.3 to 16)	0.55	0.73	-0.10 (-2.0 to 1.8)	0.92	0.92	-0.07 (-0.40 to 0.27)	0.70	0.96	0.05 (-0.31 to 0.42)	0.77	0.77
group_char		0.001	0.003		0.026	0.11		0.96	0.96		0.44	0.58
H1000’s	—			—			—			—
H2000’s	54 (23 to 84)			-0.77 (-6.1 to 4.5)			-0.15 (-1.2 to 0.87)			0.80 (-0.43 to 2.0)
H3000’s	1.4 (-26 to 29)			6.1 (1.2 to 11)			-0.07 (-1.0 to 0.89)			0.18 (-0.97 to 1.3)
mean_StanceDur * group_char		<0.001	<0.001		0.087	0.17		0.93	0.96		0.26	0.52
mean_StanceDur * H2000’s	-61 (-88 to -35)			-0.58 (-4.9 to 3.8)			0.07 (-0.69 to 0.82)			0.69 (-0.14 to 1.5)
mean_StanceDur * H3000’s	-3.9 (-29 to 21)			-4.8 (-9.2 to -0.54)			0.15 (-0.61 to 0.91)			0.03 (-0.80 to 0.86)
subj_char.sd__(Intercept)	0.00 (NA to NA)			2.6 (NA to NA)			0.77 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	30 (NA to NA)			4.8 (NA to NA)			0.82 (NA to NA)			0.89 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_offset for Cluster: 13
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-3.8 (-23 to 16)	0.71	0.71	0.67 (-2.7 to 4.0)	0.70	0.92	-0.19 (-0.83 to 0.45)	0.56	0.92	0.87 (0.10 to 1.6)	0.027	0.11
mean_GaitCycleDur	3.2 (-6.8 to 13)	0.54	0.71	-0.08 (-1.7 to 1.5)	0.92	0.92	-0.05 (-0.33 to 0.23)	0.72	0.92	0.04 (-0.26 to 0.34)	0.81	0.81
group_char		0.003	0.006		0.034	0.14		0.92	0.92		0.67	0.81
H1000’s	—			—			—			—
H2000’s	63 (26 to 100)			-0.51 (-6.9 to 5.9)			-0.23 (-1.4 to 0.97)			0.63 (-0.76 to 2.0)
H3000’s	4.8 (-28 to 38)			7.2 (1.4 to 13)			-0.17 (-1.3 to 0.94)			0.14 (-1.2 to 1.4)
mean_GaitCycleDur * group_char		<0.001	<0.001		0.088	0.18		0.85	0.92		0.28	0.57
mean_GaitCycleDur * H2000’s	-47 (-70 to -25)			-0.56 (-4.2 to 3.1)			0.09 (-0.55 to 0.74)			0.57 (-0.14 to 1.3)
mean_GaitCycleDur * H3000’s	-4.9 (-26 to 16)			-4.0 (-7.6 to -0.44)			0.17 (-0.47 to 0.81)			0.05 (-0.66 to 0.75)
subj_char.sd__(Intercept)	0.00 (NA to NA)			2.6 (NA to NA)			0.77 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	30 (NA to NA)			4.8 (NA to NA)			0.82 (NA to NA)			0.89 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in NA for Cluster: 13
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	8.6 (-7.6 to 25)	0.30	0.38	0.43 (-2.4 to 3.2)	0.76	0.93	-0.36 (-0.91 to 0.18)	0.19	0.49	0.99 (0.31 to 1.7)	0.004	0.017
mean_PeakUpDownVel_mean	-27 (-89 to 34)	0.38	0.38	0.42 (-9.5 to 10)	0.93	0.93	0.33 (-1.3 to 2.0)	0.69	0.69	-0.24 (-2.1 to 1.6)	0.80	0.87
group_char		0.048	0.19		0.74	0.93		0.64	0.69		0.015	0.030
H1000’s	—			—			—			—
H2000’s	-33 (-59 to -6.7)			-1.6 (-6.2 to 2.9)			0.38 (-0.51 to 1.3)			1.6 (0.50 to 2.7)
H3000’s	-10 (-35 to 14)			-0.04 (-4.3 to 4.2)			-0.03 (-0.87 to 0.81)			0.39 (-0.65 to 1.4)
mean_PeakUpDownVel_mean * group_char		0.18	0.35		0.65	0.93		0.24	0.49		0.87	0.87
mean_PeakUpDownVel_mean * H2000’s	89 (-5.3 to 184)			1.1 (-14 to 16)			-1.7 (-4.3 to 0.84)			-0.40 (-3.3 to 2.5)
mean_PeakUpDownVel_mean * H3000’s	29 (-59 to 116)			6.4 (-7.9 to 21)			0.43 (-2.0 to 2.9)			-0.74 (-3.4 to 2.0)
subj_char.sd__(Intercept)	4.7 (NA to NA)			2.4 (NA to NA)			0.77 (NA to NA)			1.1 (NA to NA)
Residual.sd__Observation	31 (NA to NA)			4.9 (NA to NA)			0.82 (NA to NA)			0.90 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

LME EEG ~ 1+kin+group

Changes in theta_avg_power for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-4.5 (-25 to 16)	0.67	0.67	0.03 (-0.77 to 0.83)	0.94	0.94	-0.74 (-1.2 to -0.24)	0.004	0.011	1.1 (0.44 to 1.9)	0.002	0.005
mean_APexc_COV	0.47 (-0.66 to 1.6)	0.41	0.62	0.01 (-0.03 to 0.06)	0.52	0.77	0.00 (-0.02 to 0.03)	0.86	0.86	0.00 (-0.03 to 0.03)	0.91	0.91
group_char		0.14	0.41		0.43	0.77		0.47	0.70		0.12	0.19
H1000’s	—			—			—			—
H2000’s	-16 (-33 to 0.19)			-0.24 (-0.88 to 0.40)			0.29 (-0.23 to 0.80)			0.85 (-0.04 to 1.7)
H3000’s	-13 (-31 to 4.7)			0.17 (-0.52 to 0.86)			0.27 (-0.25 to 0.80)			0.70 (-0.19 to 1.6)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.74 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	53 (NA to NA)			2.1 (NA to NA)			0.93 (NA to NA)			1.0 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in alpha_avg_power for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	5.4 (-18 to 29)	0.65	0.83	1.0 (0.10 to 1.9)	0.030	0.089	-0.66 (-1.2 to -0.13)	0.014	0.043	0.91 (0.18 to 1.6)	0.015	0.045
mean_APexc_mean	-42 (-434 to 350)	0.83	0.83	-14 (-29 to 1.6)	0.080	0.12	-0.82 (-8.6 to 7.0)	0.84	0.84	4.9 (-3.8 to 14)	0.27	0.27
group_char		0.20	0.59		0.44	0.44		0.41	0.62		0.074	0.11
H1000’s	—			—			—			—
H2000’s	-14 (-29 to 1.6)			-0.29 (-0.89 to 0.31)			0.29 (-0.21 to 0.79)			0.91 (0.03 to 1.8)
H3000’s	-9.5 (-25 to 6.3)			0.10 (-0.51 to 0.71)			0.28 (-0.21 to 0.77)			0.78 (-0.08 to 1.6)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.74 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	53 (NA to NA)			2.1 (NA to NA)			0.93 (NA to NA)			1.0 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_avg_power for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-14 (-34 to 5.8)	0.16	0.21	-0.02 (-0.79 to 0.76)	0.97	0.97	-0.69 (-1.2 to -0.20)	0.006	0.018	1.5 (0.77 to 2.2)	<0.001	<0.001
mean_MLexc_COV	1.2 (-0.02 to 2.4)	0.054	0.16	0.02 (-0.03 to 0.07)	0.42	0.63	0.00 (-0.03 to 0.03)	0.93	0.93	-0.02 (-0.05 to 0.01)	0.19	0.19
group_char		0.21	0.21		0.34	0.63		0.37	0.55		0.10	0.15
H1000’s	—			—			—			—
H2000’s	-13 (-28 to 2.0)			-0.15 (-0.73 to 0.44)			0.30 (-0.19 to 0.79)			0.85 (-0.02 to 1.7)
H3000’s	-8.6 (-23 to 6.0)			0.31 (-0.26 to 0.88)			0.29 (-0.19 to 0.77)			0.71 (-0.14 to 1.6)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.74 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	53 (NA to NA)			2.1 (NA to NA)			0.93 (NA to NA)			1.0 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_div_theta for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	14 (-4.2 to 31)	0.13	0.23	0.63 (-0.07 to 1.3)	0.077	0.23	-0.80 (-1.2 to -0.37)	<0.001	<0.001	0.91 (0.26 to 1.6)	0.006	0.018
mean_MLexc_mean	-129 (-315 to 56)	0.17	0.23	-4.4 (-12 to 2.8)	0.23	0.34	1.2 (-2.6 to 4.9)	0.54	0.54	3.3 (-0.85 to 7.4)	0.12	0.12
group_char		0.23	0.23		0.37	0.37		0.38	0.54		0.11	0.12
H1000’s	—			—			—			—
H2000’s	-12 (-28 to 2.5)			-0.12 (-0.71 to 0.46)			0.29 (-0.20 to 0.78)			0.84 (-0.03 to 1.7)
H3000’s	-8.7 (-23 to 5.9)			0.31 (-0.26 to 0.88)			0.29 (-0.19 to 0.77)			0.71 (-0.14 to 1.6)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.73 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	53 (NA to NA)			2.1 (NA to NA)			0.93 (NA to NA)			0.99 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_div_beta for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	7.8 (-24 to 40)	0.64	0.76	0.82 (-0.10 to 1.7)	0.080	0.24	-0.53 (-1.1 to 0.02)	0.057	0.17	0.78 (0.07 to 1.5)	0.031	0.078
mean_StepDur	-5.1 (-37 to 27)	0.76	0.76	-0.60 (-1.5 to 0.31)	0.20	0.30	-0.20 (-0.67 to 0.27)	0.40	0.60	0.43 (-0.05 to 0.91)	0.078	0.078
group_char		0.34	0.76		0.44	0.44		0.60	0.60		0.061	0.078
H1000’s	—			—			—			—
H2000’s	-14 (-35 to 6.8)			-0.25 (-0.85 to 0.35)			0.27 (-0.26 to 0.80)			0.93 (0.04 to 1.8)
H3000’s	-0.50 (-22 to 21)			0.16 (-0.45 to 0.76)			0.16 (-0.36 to 0.69)			0.86 (-0.01 to 1.7)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.79 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	72 (NA to NA)			2.1 (NA to NA)			1.0 (NA to NA)			1.0 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_beta_div_theta for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	9.0 (-8.0 to 26)	0.30	0.41	0.49 (-0.17 to 1.1)	0.15	0.42	-0.71 (-1.1 to -0.30)	<0.001	0.002	1.1 (0.46 to 1.7)	<0.001	0.002
mean_UDexc_COV	-0.47 (-1.6 to 0.64)	0.41	0.41	-0.02 (-0.06 to 0.03)	0.42	0.42	0.00 (-0.02 to 0.02)	0.99	0.99	0.01 (-0.02 to 0.03)	0.53	0.53
group_char		0.22	0.41		0.32	0.42		0.37	0.55		0.10	0.16
H1000’s	—			—			—			—
H2000’s	-13 (-28 to 2.1)			-0.14 (-0.72 to 0.45)			0.30 (-0.19 to 0.79)			0.86 (-0.02 to 1.7)
H3000’s	-8.3 (-23 to 6.4)			0.32 (-0.25 to 0.89)			0.29 (-0.19 to 0.77)			0.70 (-0.15 to 1.6)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.74 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	53 (NA to NA)			2.1 (NA to NA)			0.93 (NA to NA)			1.0 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_theta_div_beta for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-11 (-29 to 7.7)	0.26	0.26	0.02 (-0.70 to 0.74)	0.95	0.95	-0.85 (-1.3 to -0.41)	<0.001	<0.001	1.5 (0.89 to 2.2)	<0.001	<0.001
mean_UDexc_mean	579 (-85 to 1,242)	0.087	0.25	10 (-16 to 36)	0.44	0.65	5.9 (-6.9 to 19)	0.37	0.38	-15 (-29 to -1.2)	0.034	0.051
group_char		0.17	0.25		0.36	0.65		0.38	0.38		0.091	0.091
H1000’s	—			—			—			—
H2000’s	-14 (-29 to 1.3)			-0.16 (-0.74 to 0.42)			0.30 (-0.19 to 0.79)			0.87 (0.00 to 1.7)
H3000’s	-9.6 (-24 to 5.0)			0.29 (-0.28 to 0.86)			0.28 (-0.20 to 0.76)			0.73 (-0.11 to 1.6)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.73 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	53 (NA to NA)			2.1 (NA to NA)			0.93 (NA to NA)			0.99 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_exp for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	6.5 (-21 to 34)	0.64	0.78	0.76 (-0.02 to 1.5)	0.056	0.17	-0.58 (-1.1 to -0.10)	0.017	0.052	0.86 (0.20 to 1.5)	0.011	0.033
mean_StanceDur	-2.8 (-22 to 17)	0.78	0.78	-0.39 (-0.94 to 0.16)	0.16	0.24	-0.10 (-0.38 to 0.18)	0.47	0.57	0.25 (-0.03 to 0.53)	0.081	0.081
group_char		0.34	0.78		0.42	0.42		0.57	0.57		0.066	0.081
H1000’s	—			—			—			—
H2000’s	-14 (-35 to 6.9)			-0.24 (-0.84 to 0.35)			0.28 (-0.25 to 0.81)			0.92 (0.03 to 1.8)
H3000’s	-0.20 (-21 to 21)			0.17 (-0.42 to 0.76)			0.18 (-0.34 to 0.70)			0.84 (-0.03 to 1.7)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.79 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	72 (NA to NA)			2.1 (NA to NA)			1.0 (NA to NA)			1.0 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_offset for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	7.7 (-24 to 40)	0.64	0.76	0.81 (-0.10 to 1.7)	0.081	0.24	-0.53 (-1.1 to 0.02)	0.057	0.17	0.78 (0.07 to 1.5)	0.031	0.078
mean_GaitCycleDur	-2.5 (-19 to 14)	0.76	0.76	-0.30 (-0.76 to 0.16)	0.20	0.30	-0.10 (-0.33 to 0.13)	0.40	0.60	0.21 (-0.02 to 0.45)	0.078	0.078
group_char		0.34	0.76		0.44	0.44		0.60	0.60		0.062	0.078
H1000’s	—			—			—			—
H2000’s	-14 (-35 to 6.8)			-0.25 (-0.85 to 0.35)			0.27 (-0.26 to 0.80)			0.93 (0.03 to 1.8)
H3000’s	-0.49 (-22 to 21)			0.16 (-0.45 to 0.76)			0.16 (-0.36 to 0.69)			0.86 (-0.01 to 1.7)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.79 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	72 (NA to NA)			2.1 (NA to NA)			1.0 (NA to NA)			1.0 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in NA for Cluster: 8
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-6.6 (-22 to 8.9)	0.40	0.40	0.01 (-0.60 to 0.61)	0.98	0.98	-0.81 (-1.2 to -0.42)	<0.001	<0.001	1.4 (0.84 to 2.0)	<0.001	<0.001
mean_PeakUpDownVel_mean	41 (-11 to 93)	0.12	0.21	1.1 (-0.93 to 3.1)	0.29	0.57	0.42 (-0.54 to 1.4)	0.39	0.40	-1.1 (-2.2 to -0.11)	0.030	0.045
group_char		0.14	0.21		0.38	0.57		0.40	0.40		0.081	0.081
H1000’s	—			—			—			—
H2000’s	-14 (-29 to 0.72)			-0.18 (-0.76 to 0.41)			0.29 (-0.20 to 0.78)			0.89 (0.02 to 1.8)
H3000’s	-10 (-25 to 4.4)			0.26 (-0.31 to 0.83)			0.28 (-0.21 to 0.76)			0.76 (-0.09 to 1.6)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.73 (NA to NA)			1.5 (NA to NA)
Residual.sd__Observation	53 (NA to NA)			2.1 (NA to NA)			0.93 (NA to NA)			0.99 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_avg_power for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-5.7 (-16 to 4.7)	0.28	0.49	5.2 (-2.8 to 13)	0.20	0.61	-0.27 (-0.90 to 0.36)	0.40	0.60	1.4 (0.62 to 2.2)	<0.001	0.001
mean_APexc_COV	0.04 (-0.51 to 0.59)	0.87	0.87	-0.18 (-0.59 to 0.24)	0.41	0.61	0.01 (-0.02 to 0.04)	0.40	0.60	-0.03 (-0.06 to 0.01)	0.14	0.21
group_char		0.33	0.49		0.82	0.82		0.91	0.91		0.32	0.32
H1000’s	—			—			—			—
H2000’s	7.0 (-2.3 to 16)			-0.55 (-8.0 to 6.9)			-0.14 (-0.76 to 0.48)			0.64 (-0.21 to 1.5)
H3000’s	5.2 (-4.0 to 14)			1.6 (-5.8 to 8.9)			-0.10 (-0.70 to 0.50)			0.20 (-0.61 to 1.0)
subj_char.sd__(Intercept)	2.6 (NA to NA)			4.6 (NA to NA)			0.50 (NA to NA)			0.87 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in alpha_avg_power for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-1.2 (-14 to 12)	0.86	0.86	-3.3 (-13 to 6.6)	0.51	0.76	0.05 (-0.71 to 0.81)	0.89	0.97	1.3 (0.43 to 2.2)	0.004	0.011
mean_APexc_mean	-67 (-278 to 143)	0.53	0.80	102 (-52 to 256)	0.20	0.59	-2.0 (-13 to 9.5)	0.73	0.97	-5.6 (-18 to 6.4)	0.36	0.46
group_char		0.36	0.80		0.82	0.82		0.97	0.97		0.46	0.46
H1000’s	—			—			—			—
H2000’s	6.4 (-2.6 to 15)			-0.35 (-7.4 to 6.7)			-0.08 (-0.67 to 0.52)			0.40 (-0.44 to 1.2)
H3000’s	4.5 (-3.9 to 13)			1.6 (-5.0 to 8.2)			-0.02 (-0.57 to 0.54)			-0.09 (-0.87 to 0.69)
subj_char.sd__(Intercept)	2.1 (NA to NA)			3.9 (NA to NA)			0.47 (NA to NA)			0.88 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_avg_power for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-8.5 (-20 to 3.0)	0.15	0.29	5.8 (-3.1 to 15)	0.20	0.57	-0.48 (-1.2 to 0.21)	0.17	0.25	1.3 (0.42 to 2.1)	0.003	0.010
mean_MLexc_COV	0.24 (-0.43 to 0.90)	0.49	0.49	-0.22 (-0.73 to 0.28)	0.38	0.57	0.03 (-0.01 to 0.07)	0.14	0.25	-0.02 (-0.06 to 0.02)	0.41	0.41
group_char		0.19	0.29		0.87	0.87		0.95	0.95		0.41	0.41
H1000’s	—			—			—			—
H2000’s	7.3 (-1.2 to 16)			-1.7 (-8.7 to 5.2)			-0.05 (-0.62 to 0.53)			0.47 (-0.35 to 1.3)
H3000’s	5.8 (-2.1 to 14)			-0.17 (-6.6 to 6.3)			0.05 (-0.49 to 0.59)			-0.03 (-0.79 to 0.73)
subj_char.sd__(Intercept)	2.3 (NA to NA)			4.5 (NA to NA)			0.49 (NA to NA)			0.87 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_div_theta for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-2.6 (-12 to 7.1)	0.60	0.60	-1.3 (-8.7 to 6.0)	0.72	0.85	0.15 (-0.43 to 0.73)	0.61	0.91	1.0 (0.30 to 1.7)	0.006	0.017
mean_MLexc_mean	-30 (-127 to 67)	0.55	0.60	47 (-24 to 119)	0.20	0.59	-2.7 (-8.0 to 2.7)	0.33	0.91	-0.36 (-6.0 to 5.3)	0.90	0.90
group_char		0.18	0.55		0.85	0.85		0.96	0.96		0.43	0.65
H1000’s	—			—			—			—
H2000’s	7.4 (-1.1 to 16)			-1.9 (-8.7 to 4.9)			-0.04 (-0.61 to 0.54)			0.47 (-0.35 to 1.3)
H3000’s	5.9 (-2.1 to 14)			-0.47 (-6.8 to 5.9)			0.05 (-0.49 to 0.58)			-0.01 (-0.77 to 0.76)
subj_char.sd__(Intercept)	2.2 (NA to NA)			4.2 (NA to NA)			0.48 (NA to NA)			0.88 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_div_beta for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-6.6 (-20 to 6.6)	0.33	0.49	-3.4 (-13 to 6.3)	0.49	0.74	0.09 (-0.64 to 0.83)	0.80	0.96	1.3 (0.51 to 2.2)	0.002	0.005
mean_StepDur	1.7 (-11 to 14)	0.79	0.79	6.3 (-2.9 to 15)	0.18	0.54	-0.17 (-0.83 to 0.50)	0.62	0.96	-0.38 (-1.1 to 0.29)	0.27	0.40
group_char		0.21	0.49		0.80	0.80		0.96	0.96		0.44	0.44
H1000’s	—			—			—			—
H2000’s	7.6 (-1.2 to 16)			-0.56 (-7.5 to 6.4)			-0.08 (-0.66 to 0.51)			0.40 (-0.43 to 1.2)
H3000’s	6.0 (-2.4 to 14)			1.6 (-5.0 to 8.2)			-0.03 (-0.58 to 0.52)			-0.10 (-0.88 to 0.68)
subj_char.sd__(Intercept)	2.3 (NA to NA)			4.0 (NA to NA)			0.48 (NA to NA)			0.88 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_beta_div_theta for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-5.2 (-15 to 4.4)	0.29	0.43	-1.6 (-8.8 to 5.7)	0.67	0.81	0.09 (-0.48 to 0.65)	0.77	0.97	1.1 (0.42 to 1.8)	0.002	0.005
mean_UDexc_COV	0.01 (-0.60 to 0.63)	0.96	0.96	0.33 (-0.12 to 0.77)	0.15	0.46	-0.01 (-0.04 to 0.02)	0.48	0.97	-0.01 (-0.04 to 0.02)	0.55	0.55
group_char		0.21	0.43		0.81	0.81		0.97	0.97		0.42	0.55
H1000’s	—			—			—			—
H2000’s	7.2 (-1.3 to 16)			-2.2 (-9.0 to 4.7)			-0.03 (-0.61 to 0.54)			0.49 (-0.34 to 1.3)
H3000’s	5.5 (-2.5 to 13)			-0.40 (-6.8 to 6.0)			0.03 (-0.50 to 0.57)			0.01 (-0.76 to 0.77)
subj_char.sd__(Intercept)	2.3 (NA to NA)			4.3 (NA to NA)			0.48 (NA to NA)			0.87 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_theta_div_beta for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-4.8 (-15 to 5.5)	0.36	0.54	6.9 (-0.88 to 15)	0.083	0.25	-0.34 (-0.94 to 0.26)	0.27	0.40	1.0 (0.30 to 1.8)	0.006	0.018
mean_UDexc_mean	-8.6 (-363 to 346)	0.96	0.96	-182 (-441 to 76)	0.17	0.25	11 (-7.6 to 31)	0.24	0.40	-1.8 (-22 to 18)	0.86	0.86
group_char		0.20	0.54		0.80	0.80		0.99	0.99		0.43	0.65
H1000’s	—			—			—			—
H2000’s	7.2 (-1.3 to 16)			-1.8 (-8.6 to 5.0)			-0.04 (-0.61 to 0.52)			0.47 (-0.35 to 1.3)
H3000’s	5.5 (-2.4 to 13)			0.29 (-6.0 to 6.6)			0.00 (-0.52 to 0.53)			-0.01 (-0.77 to 0.76)
subj_char.sd__(Intercept)	2.4 (NA to NA)			4.2 (NA to NA)			0.46 (NA to NA)			0.88 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_exp for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-6.7 (-18 to 4.7)	0.25	0.37	-2.1 (-11 to 6.3)	0.62	0.82	0.05 (-0.59 to 0.69)	0.88	0.97	1.3 (0.56 to 2.1)	<0.001	0.002
mean_StanceDur	1.3 (-6.3 to 8.9)	0.74	0.74	3.6 (-1.9 to 9.1)	0.20	0.60	-0.09 (-0.48 to 0.31)	0.67	0.97	-0.25 (-0.65 to 0.15)	0.22	0.33
group_char		0.19	0.37		0.82	0.82		0.97	0.97		0.44	0.44
H1000’s	—			—			—			—
H2000’s	7.6 (-1.1 to 16)			-0.77 (-7.7 to 6.1)			-0.07 (-0.65 to 0.51)			0.41 (-0.42 to 1.2)
H3000’s	6.0 (-2.2 to 14)			1.3 (-5.2 to 7.8)			-0.02 (-0.56 to 0.53)			-0.10 (-0.87 to 0.68)
subj_char.sd__(Intercept)	2.3 (NA to NA)			4.0 (NA to NA)			0.48 (NA to NA)			0.88 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_offset for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-6.6 (-20 to 6.6)	0.33	0.49	-3.4 (-13 to 6.3)	0.49	0.74	0.09 (-0.64 to 0.83)	0.80	0.96	1.4 (0.51 to 2.2)	0.002	0.005
mean_GaitCycleDur	0.86 (-5.5 to 7.2)	0.79	0.79	3.1 (-1.4 to 7.7)	0.18	0.54	-0.08 (-0.42 to 0.25)	0.62	0.96	-0.19 (-0.53 to 0.14)	0.26	0.40
group_char		0.21	0.49		0.80	0.80		0.96	0.96		0.44	0.44
H1000’s	—			—			—			—
H2000’s	7.6 (-1.2 to 16)			-0.56 (-7.5 to 6.4)			-0.08 (-0.66 to 0.51)			0.40 (-0.43 to 1.2)
H3000’s	6.0 (-2.4 to 14)			1.6 (-5.0 to 8.2)			-0.03 (-0.58 to 0.52)			-0.10 (-0.88 to 0.68)
subj_char.sd__(Intercept)	2.3 (NA to NA)			4.0 (NA to NA)			0.48 (NA to NA)			0.88 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in NA for Cluster: 9
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-6.0 (-15 to 2.8)	0.18	0.32	5.9 (-0.70 to 13)	0.080	0.24	-0.17 (-0.69 to 0.35)	0.52	0.81	1.0 (0.35 to 1.7)	0.003	0.008
mean_PeakUpDownVel_mean	4.0 (-24 to 32)	0.78	0.78	-14 (-35 to 5.6)	0.16	0.24	0.46 (-1.0 to 1.9)	0.54	0.81	-0.09 (-1.6 to 1.4)	0.91	0.91
group_char		0.21	0.32		0.84	0.84		0.97	0.97		0.43	0.64
H1000’s	—			—			—			—
H2000’s	7.2 (-1.4 to 16)			-1.5 (-8.2 to 5.3)			-0.06 (-0.63 to 0.52)			0.47 (-0.35 to 1.3)
H3000’s	5.4 (-2.5 to 13)			0.45 (-5.8 to 6.7)			0.00 (-0.53 to 0.53)			-0.01 (-0.77 to 0.76)
subj_char.sd__(Intercept)	2.5 (NA to NA)			4.0 (NA to NA)			0.47 (NA to NA)			0.88 (NA to NA)
Residual.sd__Observation	21 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			1.1 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_avg_power for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	6.3 (-5.6 to 18)	0.30	0.45	0.60 (-7.8 to 9.0)	0.89	0.94	0.08 (-0.62 to 0.79)	0.81	0.81	0.25 (-0.44 to 0.95)	0.48	0.48
mean_APexc_COV	-0.17 (-0.78 to 0.44)	0.58	0.58	0.01 (-0.38 to 0.41)	0.94	0.94	-0.02 (-0.05 to 0.02)	0.33	0.81	0.03 (0.00 to 0.05)	0.083	0.12
group_char		0.016	0.048		0.38	0.94		0.69	0.81		0.052	0.12
H1000’s	—			—			—			—
H2000’s	-9.6 (-20 to 0.93)			3.8 (-4.8 to 12)			0.26 (-0.47 to 0.99)			0.97 (0.16 to 1.8)
H3000’s	5.4 (-5.2 to 16)			-2.2 (-10 to 6.0)			0.27 (-0.42 to 0.97)			0.65 (-0.11 to 1.4)
subj_char.sd__(Intercept)	6.9 (NA to NA)			8.7 (NA to NA)			0.77 (NA to NA)			0.95 (NA to NA)
Residual.sd__Observation	23 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.91 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in alpha_avg_power for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	18 (4.3 to 32)	0.010	0.015	1.0 (-8.2 to 10)	0.83	0.97	0.19 (-0.57 to 0.95)	0.62	0.93	0.38 (-0.36 to 1.1)	0.31	0.31
mean_APexc_mean	-273 (-502 to -44)	0.019	0.019	-2.7 (-144 to 139)	0.97	0.97	-7.1 (-19 to 4.6)	0.23	0.70	5.6 (-4.4 to 16)	0.27	0.31
group_char		0.009	0.015		0.37	0.97		0.97	0.97		0.007	0.021
H1000’s	—			—			—			—
H2000’s	-14 (-24 to -3.4)			3.8 (-4.7 to 12)			0.09 (-0.62 to 0.81)			1.2 (0.35 to 2.0)
H3000’s	0.66 (-8.4 to 9.8)			-2.1 (-9.5 to 5.3)			0.04 (-0.59 to 0.67)			0.96 (0.23 to 1.7)
subj_char.sd__(Intercept)	6.7 (NA to NA)			8.7 (NA to NA)			0.75 (NA to NA)			0.97 (NA to NA)
Residual.sd__Observation	23 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.91 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_avg_power for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	1.9 (-11 to 15)	0.77	0.78	-3.0 (-12 to 5.9)	0.51	0.51	0.52 (-0.21 to 1.3)	0.16	0.24	0.55 (-0.19 to 1.3)	0.14	0.22
mean_MLexc_COV	0.11 (-0.67 to 0.89)	0.78	0.78	0.26 (-0.24 to 0.76)	0.30	0.49	-0.05 (-0.09 to -0.01)	0.018	0.055	0.01 (-0.03 to 0.05)	0.63	0.63
group_char		0.021	0.064		0.33	0.49		0.92	0.92		0.010	0.030
H1000’s	—			—			—			—
H2000’s	-10 (-20 to -0.18)			4.3 (-4.1 to 13)			0.10 (-0.61 to 0.80)			1.1 (0.30 to 1.9)
H3000’s	3.8 (-5.0 to 13)			-2.1 (-9.3 to 5.2)			0.12 (-0.49 to 0.73)			0.89 (0.18 to 1.6)
subj_char.sd__(Intercept)	6.7 (NA to NA)			8.8 (NA to NA)			0.75 (NA to NA)			0.97 (NA to NA)
Residual.sd__Observation	23 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.91 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_div_theta for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	13 (2.8 to 24)	0.013	0.021	6.7 (-0.56 to 14)	0.071	0.11	-0.28 (-0.89 to 0.33)	0.37	0.88	0.46 (-0.17 to 1.1)	0.15	0.23
mean_MLexc_mean	-120 (-222 to -19)	0.020	0.021	-72 (-135 to -8.8)	0.026	0.077	1.2 (-4.1 to 6.5)	0.67	0.88	2.7 (-1.8 to 7.3)	0.24	0.24
group_char		0.021	0.021		0.36	0.36		0.88	0.88		0.012	0.037
H1000’s	—			—			—			—
H2000’s	-9.7 (-20 to 0.45)			4.3 (-3.9 to 12)			0.17 (-0.53 to 0.87)			1.1 (0.27 to 1.9)
H3000’s	4.5 (-4.4 to 13)			-1.6 (-8.8 to 5.6)			0.11 (-0.50 to 0.72)			0.88 (0.16 to 1.6)
subj_char.sd__(Intercept)	7.4 (NA to NA)			8.6 (NA to NA)			0.74 (NA to NA)			0.97 (NA to NA)
Residual.sd__Observation	22 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.91 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_div_beta for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	16 (2.0 to 30)	0.025	0.038	4.1 (-5.0 to 13)	0.38	0.39	-0.13 (-0.88 to 0.62)	0.73	0.89	0.31 (-0.41 to 1.0)	0.40	0.40
mean_StepDur	-14 (-27 to -0.02)	0.050	0.050	-3.5 (-12 to 4.6)	0.39	0.39	-0.06 (-0.73 to 0.61)	0.87	0.89	0.41 (-0.15 to 0.97)	0.15	0.23
group_char		0.016	0.038		0.34	0.39		0.89	0.89		0.006	0.019
H1000’s	—			—			—			—
H2000’s	-13 (-23 to -2.5)			3.3 (-5.1 to 12)			0.17 (-0.54 to 0.88)			1.2 (0.35 to 2.0)
H3000’s	0.70 (-8.5 to 10)			-2.8 (-10 to 4.6)			0.11 (-0.52 to 0.74)			0.98 (0.25 to 1.7)
subj_char.sd__(Intercept)	6.9 (NA to NA)			8.7 (NA to NA)			0.75 (NA to NA)			0.98 (NA to NA)
Residual.sd__Observation	23 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.90 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_beta_div_theta for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	13 (3.4 to 24)	0.009	0.015	2.5 (-4.6 to 9.7)	0.48	0.49	-0.27 (-0.86 to 0.33)	0.37	0.88	0.38 (-0.23 to 0.99)	0.22	0.22
mean_UDexc_COV	-0.79 (-1.4 to -0.16)	0.014	0.015	-0.13 (-0.52 to 0.25)	0.49	0.49	0.01 (-0.03 to 0.04)	0.68	0.88	0.02 (0.00 to 0.05)	0.083	0.12
group_char		0.015	0.015		0.38	0.49		0.88	0.88		0.012	0.036
H1000’s	—			—			—			—
H2000’s	-10 (-20 to -0.11)			3.9 (-4.4 to 12)			0.18 (-0.53 to 0.88)			1.1 (0.28 to 1.9)
H3000’s	4.5 (-4.2 to 13)			-1.9 (-9.2 to 5.3)			0.11 (-0.50 to 0.73)			0.87 (0.16 to 1.6)
subj_char.sd__(Intercept)	6.7 (NA to NA)			8.7 (NA to NA)			0.75 (NA to NA)			0.97 (NA to NA)
Residual.sd__Observation	23 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.90 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_theta_div_beta for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-8.0 (-18 to 2.5)	0.13	0.13	-1.6 (-8.9 to 5.7)	0.67	0.67	0.11 (-0.50 to 0.72)	0.72	0.81	0.94 (0.32 to 1.6)	0.003	0.009
mean_UDexc_mean	508 (142 to 874)	0.007	0.020	108 (-117 to 334)	0.35	0.53	-13 (-32 to 5.4)	0.17	0.50	-12 (-27 to 4.2)	0.15	0.15
group_char		0.024	0.037		0.35	0.53		0.81	0.81		0.008	0.012
H1000’s	—			—			—			—
H2000’s	-12 (-22 to -1.3)			3.6 (-4.7 to 12)			0.20 (-0.50 to 0.91)			1.1 (0.31 to 1.9)
H3000’s	2.0 (-7.0 to 11)			-2.4 (-9.7 to 4.8)			0.16 (-0.46 to 0.79)			0.93 (0.22 to 1.6)
subj_char.sd__(Intercept)	7.6 (NA to NA)			8.7 (NA to NA)			0.76 (NA to NA)			0.97 (NA to NA)
Residual.sd__Observation	22 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.91 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_exp for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	13 (1.0 to 25)	0.033	0.050	3.5 (-4.4 to 11)	0.39	0.39	-0.15 (-0.81 to 0.52)	0.67	0.88	0.39 (-0.27 to 1.0)	0.25	0.25
mean_StanceDur	-7.7 (-16 to 0.51)	0.066	0.066	-2.1 (-7.0 to 2.7)	0.39	0.39	-0.03 (-0.43 to 0.37)	0.88	0.88	0.23 (-0.10 to 0.57)	0.17	0.25
group_char		0.017	0.050		0.35	0.39		0.88	0.88		0.007	0.021
H1000’s	—			—			—			—
H2000’s	-12 (-23 to -2.1)			3.3 (-5.0 to 12)			0.17 (-0.54 to 0.88)			1.2 (0.34 to 2.0)
H3000’s	1.3 (-7.8 to 10)			-2.7 (-10 to 4.7)			0.11 (-0.52 to 0.74)			0.96 (0.24 to 1.7)
subj_char.sd__(Intercept)	6.9 (NA to NA)			8.7 (NA to NA)			0.75 (NA to NA)			0.98 (NA to NA)
Residual.sd__Observation	23 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.90 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_offset for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	16 (2.1 to 30)	0.024	0.036	4.0 (-5.0 to 13)	0.38	0.39	-0.13 (-0.88 to 0.62)	0.73	0.89	0.31 (-0.41 to 1.0)	0.40	0.40
mean_GaitCycleDur	-6.9 (-14 to -0.06)	0.048	0.048	-1.8 (-5.8 to 2.3)	0.39	0.39	-0.03 (-0.36 to 0.31)	0.87	0.89	0.20 (-0.08 to 0.48)	0.15	0.23
group_char		0.016	0.036		0.34	0.39		0.89	0.89		0.006	0.019
H1000’s	—			—			—			—
H2000’s	-13 (-23 to -2.5)			3.3 (-5.1 to 12)			0.17 (-0.54 to 0.88)			1.2 (0.35 to 2.0)
H3000’s	0.69 (-8.6 to 9.9)			-2.8 (-10 to 4.6)			0.11 (-0.52 to 0.74)			0.98 (0.25 to 1.7)
subj_char.sd__(Intercept)	6.9 (NA to NA)			8.7 (NA to NA)			0.75 (NA to NA)			0.98 (NA to NA)
Residual.sd__Observation	23 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.90 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in NA for Cluster: 10
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-6.7 (-15 to 2.1)	0.13	0.13	-1.0 (-7.4 to 5.4)	0.75	0.75	0.05 (-0.48 to 0.59)	0.84	0.84	0.84 (0.26 to 1.4)	0.004	0.013
mean_PeakUpDownVel_mean	44 (17 to 71)	0.001	0.003	8.2 (-8.1 to 25)	0.32	0.53	-1.0 (-2.4 to 0.29)	0.13	0.38	-0.68 (-1.8 to 0.45)	0.24	0.24
group_char		0.018	0.027		0.35	0.53		0.80	0.84		0.008	0.013
H1000’s	—			—			—			—
H2000’s	-12 (-22 to -2.0)			3.6 (-4.7 to 12)			0.21 (-0.49 to 0.92)			1.1 (0.31 to 1.9)
H3000’s	1.5 (-7.3 to 10)			-2.5 (-9.8 to 4.8)			0.17 (-0.45 to 0.79)			0.93 (0.21 to 1.6)
subj_char.sd__(Intercept)	7.0 (NA to NA)			8.7 (NA to NA)			0.75 (NA to NA)			0.97 (NA to NA)
Residual.sd__Observation	22 (NA to NA)			13 (NA to NA)			1.1 (NA to NA)			0.91 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_avg_power for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-17 (-50 to 16)	0.32	0.32	3.3 (-2.1 to 8.7)	0.23	0.64	-0.51 (-1.0 to 0.01)	0.056	0.17	0.53 (-0.18 to 1.2)	0.15	0.22
mean_APexc_COV	1.2 (-0.60 to 3.0)	0.19	0.32	-0.07 (-0.37 to 0.22)	0.64	0.64	0.02 (-0.01 to 0.04)	0.21	0.27	0.00 (-0.03 to 0.03)	0.93	0.93
group_char		0.26	0.32		0.48	0.64		0.27	0.27		0.002	0.005
H1000’s	—			—			—			—
H2000’s	-17 (-44 to 10)			-2.0 (-6.5 to 2.4)			-0.24 (-0.72 to 0.24)			1.3 (0.56 to 2.0)
H3000’s	-26 (-58 to 5.7)			0.22 (-5.0 to 5.4)			-0.45 (-0.98 to 0.09)			1.1 (0.26 to 1.8)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.52 (NA to NA)			0.96 (NA to NA)
Residual.sd__Observation	79 (NA to NA)			13 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in alpha_avg_power for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-5.1 (-47 to 36)	0.81	0.81	0.35 (-6.4 to 7.1)	0.92	0.92	-0.20 (-0.82 to 0.41)	0.52	0.81	0.38 (-0.42 to 1.2)	0.35	0.53
mean_APexc_mean	137 (-564 to 839)	0.70	0.81	34 (-80 to 148)	0.56	0.84	-0.71 (-11 to 9.1)	0.89	0.89	3.1 (-8.9 to 15)	0.61	0.61
group_char		0.72	0.81		0.51	0.84		0.54	0.81		<0.001	0.001
H1000’s	—			—			—			—
H2000’s	-8.1 (-34 to 18)			-2.1 (-6.3 to 2.0)			-0.14 (-0.60 to 0.32)			1.3 (0.62 to 2.0)
H3000’s	-11 (-37 to 16)			-0.08 (-4.4 to 4.3)			-0.27 (-0.74 to 0.20)			1.1 (0.40 to 1.8)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.52 (NA to NA)			0.96 (NA to NA)
Residual.sd__Observation	79 (NA to NA)			13 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_avg_power for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-8.9 (-44 to 27)	0.63	0.63	3.4 (-2.3 to 9.2)	0.24	0.63	0.00 (-0.54 to 0.53)	0.99	0.99	0.51 (-0.21 to 1.2)	0.16	0.24
mean_MLexc_COV	0.79 (-1.4 to 3.0)	0.49	0.63	-0.09 (-0.45 to 0.27)	0.63	0.63	-0.02 (-0.05 to 0.01)	0.28	0.84	0.00 (-0.03 to 0.04)	0.88	0.88
group_char		0.56	0.63		0.43	0.63		0.56	0.84		<0.001	0.001
H1000’s	—			—			—			—
H2000’s	-9.1 (-34 to 16)			-2.5 (-6.5 to 1.5)			-0.14 (-0.59 to 0.31)			1.3 (0.60 to 2.0)
H3000’s	-13 (-38 to 11)			-0.52 (-4.5 to 3.5)			-0.24 (-0.69 to 0.21)			1.1 (0.37 to 1.8)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.52 (NA to NA)			0.96 (NA to NA)
Residual.sd__Observation	79 (NA to NA)			13 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_div_theta for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-0.12 (-30 to 29)	0.99	0.99	0.47 (-4.3 to 5.3)	0.85	0.85	-0.50 (-0.95 to -0.04)	0.034	0.10	0.60 (-0.03 to 1.2)	0.061	0.092
mean_MLexc_mean	30 (-269 to 328)	0.85	0.99	21 (-27 to 70)	0.39	0.59	3.1 (-1.0 to 7.3)	0.14	0.21	-0.64 (-5.7 to 4.4)	0.81	0.81
group_char		0.57	0.99		0.39	0.59		0.52	0.52		<0.001	0.001
H1000’s	—			—			—			—
H2000’s	-9.8 (-35 to 15)			-2.7 (-6.7 to 1.3)			-0.17 (-0.62 to 0.29)			1.3 (0.60 to 2.0)
H3000’s	-13 (-37 to 12)			-0.60 (-4.6 to 3.4)			-0.26 (-0.71 to 0.19)			1.1 (0.38 to 1.8)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.53 (NA to NA)			0.96 (NA to NA)
Residual.sd__Observation	79 (NA to NA)			13 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_div_beta for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-2.6 (-44 to 39)	0.90	0.90	-0.25 (-7.0 to 6.5)	0.94	0.94	-0.28 (-0.87 to 0.30)	0.34	0.87	0.46 (-0.29 to 1.2)	0.23	0.35
mean_StepDur	5.4 (-37 to 47)	0.80	0.90	2.7 (-4.1 to 9.5)	0.44	0.73	0.05 (-0.50 to 0.60)	0.87	0.87	0.10 (-0.55 to 0.75)	0.77	0.77
group_char		0.68	0.90		0.49	0.73		0.59	0.87		<0.001	0.001
H1000’s	—			—			—			—
H2000’s	-8.7 (-34 to 17)			-2.1 (-6.2 to 2.0)			-0.13 (-0.58 to 0.33)			1.3 (0.61 to 2.0)
H3000’s	-11 (-38 to 16)			0.11 (-4.3 to 4.5)			-0.24 (-0.71 to 0.23)			1.1 (0.38 to 1.8)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.52 (NA to NA)			0.95 (NA to NA)
Residual.sd__Observation	79 (NA to NA)			13 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_beta_div_theta for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-11 (-40 to 19)	0.47	0.49	2.3 (-2.5 to 7.1)	0.36	0.68	-0.61 (-1.0 to -0.17)	0.007	0.020	0.49 (-0.13 to 1.1)	0.12	0.18
mean_UDexc_COV	1.0 (-0.88 to 3.0)	0.29	0.49	-0.01 (-0.32 to 0.31)	0.97	0.97	0.03 (0.00 to 0.05)	0.024	0.036	0.01 (-0.02 to 0.04)	0.73	0.73
group_char		0.49	0.49		0.45	0.68		0.39	0.39		<0.001	0.002
H1000’s	—			—			—			—
H2000’s	-11 (-35 to 14)			-2.5 (-6.5 to 1.5)			-0.17 (-0.61 to 0.27)			1.3 (0.59 to 2.0)
H3000’s	-14 (-39 to 10)			-0.57 (-4.6 to 3.5)			-0.31 (-0.75 to 0.13)			1.1 (0.36 to 1.8)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.50 (NA to NA)			0.96 (NA to NA)
Residual.sd__Observation	79 (NA to NA)			13 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_theta_div_beta for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	25 (-5.2 to 55)	0.10	0.16	1.3 (-3.6 to 6.2)	0.59	0.68	0.22 (-0.22 to 0.67)	0.33	0.49	0.66 (0.04 to 1.3)	0.038	0.057
mean_UDexc_mean	-950 (-1,993 to 94)	0.074	0.16	36 (-135 to 207)	0.68	0.68	-20 (-34 to -5.7)	0.006	0.017	-4.6 (-22 to 12)	0.59	0.59
group_char		0.65	0.65		0.45	0.68		0.62	0.62		<0.001	0.001
H1000’s	—			—			—			—
H2000’s	-9.2 (-34 to 15)			-2.5 (-6.5 to 1.5)			-0.13 (-0.56 to 0.31)			1.3 (0.60 to 2.0)
H3000’s	-11 (-35 to 14)			-0.66 (-4.7 to 3.4)			-0.22 (-0.65 to 0.22)			1.1 (0.38 to 1.8)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.49 (NA to NA)			0.96 (NA to NA)
Residual.sd__Observation	79 (NA to NA)			13 (NA to NA)			0.99 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_exp for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-1.6 (-37 to 34)	0.93	0.93	0.33 (-5.4 to 6.1)	0.91	0.91	-0.29 (-0.80 to 0.22)	0.26	0.79	0.51 (-0.17 to 1.2)	0.14	0.21
mean_StanceDur	3.2 (-22 to 28)	0.80	0.93	1.5 (-2.6 to 5.6)	0.47	0.73	0.04 (-0.29 to 0.37)	0.82	0.82	0.04 (-0.35 to 0.42)	0.86	0.86
group_char		0.66	0.93		0.49	0.73		0.59	0.82		<0.001	0.001
H1000’s	—			—			—			—
H2000’s	-8.8 (-34 to 16)			-2.2 (-6.3 to 1.9)			-0.13 (-0.58 to 0.33)			1.3 (0.60 to 2.0)
H3000’s	-12 (-38 to 15)			-0.05 (-4.3 to 4.2)			-0.24 (-0.70 to 0.22)			1.1 (0.38 to 1.8)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.52 (NA to NA)			0.95 (NA to NA)
Residual.sd__Observation	79 (NA to NA)			13 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_offset for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-2.6 (-44 to 39)	0.90	0.90	-0.24 (-7.0 to 6.5)	0.94	0.94	-0.28 (-0.87 to 0.30)	0.34	0.87	0.46 (-0.29 to 1.2)	0.23	0.34
mean_GaitCycleDur	2.7 (-18 to 24)	0.80	0.90	1.3 (-2.1 to 4.7)	0.44	0.73	0.02 (-0.25 to 0.30)	0.87	0.87	0.05 (-0.27 to 0.37)	0.77	0.77
group_char		0.68	0.90		0.49	0.73		0.59	0.87		<0.001	0.001
H1000’s	—			—			—			—
H2000’s	-8.7 (-34 to 17)			-2.1 (-6.2 to 2.0)			-0.13 (-0.58 to 0.33)			1.3 (0.61 to 2.0)
H3000’s	-11 (-38 to 16)			0.11 (-4.3 to 4.5)			-0.24 (-0.71 to 0.23)			1.1 (0.38 to 1.8)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.52 (NA to NA)			0.95 (NA to NA)
Residual.sd__Observation	79 (NA to NA)			13 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in NA for Cluster: 11
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	23 (-2.8 to 48)	0.081	0.12	1.7 (-2.5 to 5.9)	0.43	0.67	0.06 (-0.34 to 0.45)	0.77	0.77	0.63 (0.06 to 1.2)	0.030	0.045
mean_PeakUpDownVel_mean	-87 (-169 to -5.2)	0.037	0.11	2.1 (-11 to 16)	0.77	0.77	-1.3 (-2.4 to -0.20)	0.020	0.060	-0.32 (-1.6 to 0.97)	0.63	0.63
group_char		0.75	0.75		0.44	0.67		0.69	0.77		<0.001	0.001
H1000’s	—			—			—			—
H2000’s	-7.7 (-32 to 17)			-2.5 (-6.6 to 1.5)			-0.11 (-0.55 to 0.33)			1.3 (0.61 to 2.0)
H3000’s	-8.6 (-33 to 16)			-0.68 (-4.7 to 3.4)			-0.20 (-0.64 to 0.25)			1.1 (0.39 to 1.8)
subj_char.sd__(Intercept)	0.00 (NA to NA)			0.00 (NA to NA)			0.51 (NA to NA)			0.96 (NA to NA)
Residual.sd__Observation	79 (NA to NA)			13 (NA to NA)			1.0 (NA to NA)			1.2 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_avg_power for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	6.1 (-12 to 25)	0.52	0.52	0.14 (-6.2 to 6.5)	0.96	0.96	-0.60 (-1.2 to -0.05)	0.033	0.10	1.4 (0.55 to 2.2)	0.001	0.003
mean_APexc_COV	-0.35 (-1.3 to 0.64)	0.49	0.52	-0.07 (-0.42 to 0.28)	0.68	0.96	0.01 (-0.01 to 0.04)	0.32	0.44	-0.01 (-0.04 to 0.02)	0.45	0.45
group_char		0.44	0.52		0.39	0.96		0.44	0.44		0.15	0.23
H1000’s	—			—			—			—
H2000’s	-2.7 (-19 to 14)			3.8 (-1.6 to 9.1)			-0.17 (-0.69 to 0.34)			0.94 (-0.05 to 1.9)
H3000’s	7.0 (-10 to 24)			2.0 (-3.6 to 7.7)			-0.34 (-0.87 to 0.18)			0.69 (-0.26 to 1.6)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.51 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	39 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.95 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in alpha_avg_power for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	9.3 (-11 to 30)	0.38	0.57	-2.0 (-9.3 to 5.4)	0.60	0.77	-0.68 (-1.3 to -0.07)	0.028	0.084	1.2 (0.42 to 2.1)	0.003	0.009
mean_APexc_mean	-159 (-488 to 171)	0.35	0.57	18 (-103 to 139)	0.77	0.77	5.6 (-3.7 to 15)	0.24	0.36	-1.3 (-10 to 7.7)	0.78	0.78
group_char		0.58	0.58		0.40	0.77		0.87	0.87		0.21	0.32
H1000’s	—			—			—			—
H2000’s	-6.3 (-22 to 9.1)			3.4 (-1.5 to 8.3)			-0.03 (-0.52 to 0.46)			0.85 (-0.12 to 1.8)
H3000’s	1.4 (-13 to 16)			1.6 (-3.3 to 6.4)			-0.12 (-0.60 to 0.35)			0.56 (-0.36 to 1.5)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.54 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	39 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.95 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_avg_power for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	6.3 (-12 to 25)	0.51	0.51	0.94 (-5.6 to 7.5)	0.78	0.78	-0.40 (-0.96 to 0.16)	0.16	0.48	1.2 (0.42 to 2.0)	0.003	0.008
mean_MLexc_COV	-0.38 (-1.5 to 0.68)	0.48	0.51	-0.13 (-0.51 to 0.25)	0.50	0.75	0.00 (-0.03 to 0.03)	0.91	0.91	0.00 (-0.03 to 0.03)	0.85	0.85
group_char		0.50	0.51		0.45	0.75		0.68	0.91		0.20	0.30
H1000’s	—			—			—			—
H2000’s	-5.4 (-21 to 9.6)			3.1 (-1.7 to 8.0)			-0.07 (-0.55 to 0.41)			0.86 (-0.11 to 1.8)
H3000’s	3.5 (-11 to 18)			1.3 (-3.3 to 5.8)			-0.20 (-0.65 to 0.25)			0.58 (-0.33 to 1.5)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.53 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	39 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.95 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in beta_div_theta for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	2.8 (-13 to 18)	0.72	0.72	-1.2 (-6.6 to 4.2)	0.67	0.94	-0.59 (-1.1 to -0.12)	0.014	0.041	1.3 (0.56 to 2.0)	<0.001	0.002
mean_MLexc_mean	-28 (-178 to 122)	0.71	0.72	2.1 (-53 to 57)	0.94	0.94	2.7 (-1.5 to 6.9)	0.21	0.32	-1.5 (-5.6 to 2.6)	0.48	0.48
group_char		0.56	0.72		0.44	0.94		0.66	0.66		0.18	0.28
H1000’s	—			—			—			—
H2000’s	-4.6 (-20 to 11)			3.2 (-1.7 to 8.2)			-0.12 (-0.61 to 0.37)			0.89 (-0.09 to 1.9)
H3000’s	3.7 (-10 to 18)			1.3 (-3.2 to 5.9)			-0.21 (-0.66 to 0.24)			0.58 (-0.33 to 1.5)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.53 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	39 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.95 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in theta_div_beta for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	5.6 (-15 to 26)	0.60	0.60	-1.0 (-8.6 to 6.5)	0.79	0.99	-0.64 (-1.2 to -0.04)	0.035	0.11	1.2 (0.41 to 2.0)	0.003	0.009
mean_StepDur	-5.4 (-25 to 14)	0.59	0.60	0.04 (-7.4 to 7.5)	0.99	0.99	0.29 (-0.25 to 0.83)	0.30	0.45	-0.03 (-0.52 to 0.46)	0.90	0.90
group_char		0.55	0.60		0.43	0.99		0.86	0.86		0.21	0.31
H1000’s	—			—			—			—
H2000’s	-5.9 (-21 to 9.4)			3.3 (-1.7 to 8.2)			-0.03 (-0.52 to 0.46)			0.86 (-0.12 to 1.8)
H3000’s	2.2 (-13 to 17)			1.3 (-3.5 to 6.2)			-0.13 (-0.60 to 0.35)			0.57 (-0.35 to 1.5)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.54 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	39 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.95 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_beta_div_theta for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	-0.34 (-16 to 15)	0.97	0.97	-1.2 (-6.6 to 4.2)	0.66	0.93	-0.55 (-1.0 to -0.10)	0.016	0.049	1.3 (0.55 to 2.0)	<0.001	0.001
mean_UDexc_COV	0.07 (-0.86 to 1.0)	0.88	0.97	0.02 (-0.34 to 0.37)	0.93	0.93	0.01 (-0.01 to 0.04)	0.27	0.40	-0.01 (-0.03 to 0.02)	0.52	0.52
group_char		0.52	0.97		0.42	0.93		0.62	0.62		0.19	0.28
H1000’s	—			—			—			—
H2000’s	-5.2 (-20 to 9.9)			3.2 (-1.6 to 8.1)			-0.09 (-0.57 to 0.39)			0.87 (-0.10 to 1.8)
H3000’s	3.5 (-11 to 18)			1.3 (-3.3 to 5.9)			-0.22 (-0.67 to 0.23)			0.59 (-0.32 to 1.5)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.52 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	39 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.95 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in log_theta_div_beta for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	4.0 (-13 to 21)	0.64	0.64	-2.0 (-7.9 to 4.0)	0.52	0.71	-0.23 (-0.72 to 0.26)	0.35	0.68	1.2 (0.41 to 1.9)	0.002	0.007
mean_UDexc_mean	-146 (-708 to 416)	0.61	0.64	40 (-169 to 250)	0.71	0.71	-6.0 (-22 to 9.7)	0.45	0.68	0.84 (-14 to 15)	0.91	0.91
group_char		0.53	0.64		0.44	0.71		0.68	0.68		0.20	0.30
H1000’s	—			—			—			—
H2000’s	-4.8 (-20 to 10)			3.2 (-1.7 to 8.0)			-0.06 (-0.54 to 0.42)			0.86 (-0.11 to 1.8)
H3000’s	3.7 (-10 to 18)			1.3 (-3.3 to 5.8)			-0.20 (-0.65 to 0.25)			0.58 (-0.33 to 1.5)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.52 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	39 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.95 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_exp for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	3.9 (-14 to 22)	0.67	0.67	-0.78 (-7.2 to 5.7)	0.81	0.94	-0.56 (-1.1 to -0.04)	0.035	0.10	1.2 (0.44 to 1.9)	0.002	0.006
mean_StanceDur	-2.7 (-14 to 9.1)	0.66	0.67	-0.19 (-4.6 to 4.3)	0.94	0.94	0.15 (-0.17 to 0.47)	0.37	0.55	-0.01 (-0.30 to 0.28)	0.93	0.93
group_char		0.55	0.67		0.44	0.94		0.82	0.82		0.20	0.30
H1000’s	—			—			—			—
H2000’s	-5.6 (-21 to 9.6)			3.2 (-1.7 to 8.1)			-0.04 (-0.53 to 0.45)			0.86 (-0.11 to 1.8)
H3000’s	2.7 (-12 to 17)			1.2 (-3.5 to 6.0)			-0.14 (-0.61 to 0.32)			0.57 (-0.34 to 1.5)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.54 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	39 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.95 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in aperiodic_offset for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	5.6 (-15 to 26)	0.60	0.60	-1.1 (-8.6 to 6.5)	0.78	0.99	-0.64 (-1.2 to -0.04)	0.035	0.11	1.2 (0.41 to 2.0)	0.003	0.009
mean_GaitCycleDur	-2.7 (-13 to 7.1)	0.58	0.60	0.02 (-3.7 to 3.7)	0.99	0.99	0.14 (-0.13 to 0.41)	0.30	0.44	-0.02 (-0.26 to 0.23)	0.90	0.90
group_char		0.55	0.60		0.43	0.99		0.86	0.86		0.20	0.31
H1000’s	—			—			—			—
H2000’s	-5.9 (-21 to 9.4)			3.3 (-1.7 to 8.2)			-0.03 (-0.52 to 0.46)			0.86 (-0.12 to 1.8)
H3000’s	2.2 (-13 to 17)			1.3 (-3.5 to 6.2)			-0.13 (-0.60 to 0.35)			0.57 (-0.35 to 1.5)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.54 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	39 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.95 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing

Changes in NA for Cluster: 12
Characteristic	BETA/THETA			THETA/BETA			log10(BETA/THETA)			log10(THETA/BETA)
	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2	Beta (95% CI)1	p-value	q-value2
(Intercept)	1.3 (-13 to 16)	0.86	0.89	-1.8 (-6.8 to 3.2)	0.49	0.70	-0.22 (-0.65 to 0.20)	0.30	0.45	1.2 (0.48 to 1.9)	<0.001	0.003
mean_PeakUpDownVel_mean	-2.9 (-46 to 40)	0.89	0.89	3.2 (-13 to 19)	0.70	0.70	-0.63 (-1.8 to 0.55)	0.30	0.45	-0.04 (-1.1 to 1.0)	0.95	0.95
group_char		0.52	0.89		0.44	0.70		0.72	0.72		0.20	0.30
H1000’s	—			—			—			—
H2000’s	-5.0 (-20 to 10)			3.2 (-1.7 to 8.0)			-0.06 (-0.54 to 0.42)			0.86 (-0.11 to 1.8)
H3000’s	3.7 (-10 to 18)			1.2 (-3.3 to 5.8)			-0.18 (-0.63 to 0.27)			0.58 (-0.33 to 1.5)
subj_char.sd__(Intercept)	13 (NA to NA)			0.00 (NA to NA)			0.52 (NA to NA)			1.4 (NA to NA)
Residual.sd__Observation	39 (NA to NA)			15 (NA to NA)			1.1 (NA to NA)			0.95 (NA to NA)
1 CI = Confidence Interval
2 False discovery rate correction for multiple testing